id	sid	tid	token	lemma	pos
ajst-30235	1	1	academic	academic	ADJ
ajst-30235	1	2	journal	journal	NOUN
ajst-30235	1	3	of	of	ADP
ajst-30235	1	4	science	science	NOUN
ajst-30235	1	5	and	and	CCONJ
ajst-30235	1	6	technology	technology	NOUN
ajst-30235	1	7	issn	issn	NOUN
ajst-30235	1	8	:	:	PUNCT
ajst-30235	1	9	2771	2771	NUM
ajst-30235	1	10	-	-	SYM
ajst-30235	1	11	3032	3032	NUM
ajst-30235	1	12	|	|	NOUN
ajst-30235	1	13	vol	vol	NOUN
ajst-30235	1	14	.	.	PUNCT
ajst-30235	2	1	14	14	NUM
ajst-30235	2	2	,	,	PUNCT
ajst-30235	2	3	no	no	INTJ
ajst-30235	2	4	.	.	NOUN
ajst-30235	2	5	3	3	NUM
ajst-30235	2	6	,	,	PUNCT
ajst-30235	2	7	2025	2025	NUM
ajst-30235	2	8	371	371	NUM
ajst-30235	2	9	bearing	bear	VERB
ajst-30235	2	10	fault	fault	NOUN
ajst-30235	2	11	diagnosis	diagnosis	NOUN
ajst-30235	2	12	method	method	NOUN
ajst-30235	2	13	based	base	VERB
ajst-30235	2	14	on	on	ADP
ajst-30235	2	15	se‐cnn	se‐cnn	PROPN
ajst-30235	2	16	taohuang	taohuang	PROPN
ajst-30235	2	17	liu	liu	PROPN
ajst-30235	2	18	,	,	PUNCT
ajst-30235	2	19	zhihua	zhihua	PROPN
ajst-30235	2	20	hu	hu	PROPN
ajst-30235	2	21	*	*	PROPN
ajst-30235	2	22	,	,	PUNCT
ajst-30235	2	23	yanyang	yanyang	PROPN
ajst-30235	2	24	zhang	zhang	PROPN
ajst-30235	2	25	,	,	PUNCT
ajst-30235	2	26	xiang	xiang	PROPN
ajst-30235	2	27	liu	liu	PROPN
ajst-30235	2	28	,	,	PUNCT
ajst-30235	2	29	sunjie	sunjie	PROPN
ajst-30235	2	30	liu	liu	PROPN
ajst-30235	2	31	,	,	PUNCT
ajst-30235	2	32	weijian	weijian	PROPN
ajst-30235	2	33	shao	shao	PROPN
ajst-30235	2	34	school	school	PROPN
ajst-30235	2	35	of	of	ADP
ajst-30235	2	36	intelligent	intelligent	ADJ
ajst-30235	2	37	manufacturing	manufacturing	NOUN
ajst-30235	2	38	and	and	CCONJ
ajst-30235	2	39	control	control	PROPN
ajst-30235	2	40	engineering	engineering	PROPN
ajst-30235	2	41	,	,	PUNCT
ajst-30235	2	42	shanghai	shanghai	PROPN
ajst-30235	2	43	polytechnic	polytechnic	PROPN
ajst-30235	2	44	university	university	PROPN
ajst-30235	2	45	,	,	PUNCT
ajst-30235	2	46	shanghai	shanghai	PROPN
ajst-30235	2	47	,	,	PUNCT
ajst-30235	2	48	201209	201209	NUM
ajst-30235	2	49	,	,	PUNCT
ajst-30235	2	50	china	china	PROPN
ajst-30235	2	51	*	*	PUNCT
ajst-30235	2	52	corresponding	correspond	VERB
ajst-30235	2	53	author	author	NOUN
ajst-30235	2	54	:	:	PUNCT
ajst-30235	2	55	zhihua	zhihua	PROPN
ajst-30235	2	56	hu	hu	PROPN
ajst-30235	2	57	(	(	PUNCT
ajst-30235	2	58	email	email	NOUN
ajst-30235	2	59	:	:	PUNCT
ajst-30235	2	60	zhhu@sspu.edu.cn	zhhu@sspu.edu.cn	X
ajst-30235	2	61	)	)	PUNCT
ajst-30235	2	62	abstract	abstract	NOUN
ajst-30235	2	63	:	:	PUNCT
ajst-30235	2	64	as	as	ADP
ajst-30235	2	65	a	a	DET
ajst-30235	2	66	key	key	ADJ
ajst-30235	2	67	component	component	NOUN
ajst-30235	2	68	in	in	ADP
ajst-30235	2	69	rotating	rotate	VERB
ajst-30235	2	70	machinery	machinery	NOUN
ajst-30235	2	71	,	,	PUNCT
ajst-30235	2	72	the	the	DET
ajst-30235	2	73	health	health	NOUN
ajst-30235	2	74	condition	condition	NOUN
ajst-30235	2	75	of	of	ADP
ajst-30235	2	76	rolling	rolling	ADJ
ajst-30235	2	77	bearings	bearing	NOUN
ajst-30235	2	78	directly	directly	ADV
ajst-30235	2	79	affects	affect	VERB
ajst-30235	2	80	the	the	DET
ajst-30235	2	81	operational	operational	ADJ
ajst-30235	2	82	efficiency	efficiency	NOUN
ajst-30235	2	83	and	and	CCONJ
ajst-30235	2	84	safety	safety	NOUN
ajst-30235	2	85	of	of	ADP
ajst-30235	2	86	the	the	DET
ajst-30235	2	87	equipment	equipment	NOUN
ajst-30235	2	88	.	.	PUNCT
ajst-30235	3	1	traditional	traditional	ADJ
ajst-30235	3	2	bearing	bear	VERB
ajst-30235	3	3	fault	fault	NOUN
ajst-30235	3	4	diagnosis	diagnosis	NOUN
ajst-30235	3	5	methods	method	NOUN
ajst-30235	3	6	rely	rely	VERB
ajst-30235	3	7	on	on	ADP
ajst-30235	3	8	signal	signal	ADJ
ajst-30235	3	9	processing	processing	NOUN
ajst-30235	3	10	techniques	technique	NOUN
ajst-30235	3	11	and	and	CCONJ
ajst-30235	3	12	empirical	empirical	ADJ
ajst-30235	3	13	feature	feature	NOUN
ajst-30235	3	14	extraction	extraction	NOUN
ajst-30235	3	15	,	,	PUNCT
ajst-30235	3	16	but	but	CCONJ
ajst-30235	3	17	in	in	ADP
ajst-30235	3	18	practical	practical	ADJ
ajst-30235	3	19	applications	application	NOUN
ajst-30235	3	20	,	,	PUNCT
ajst-30235	3	21	with	with	ADP
ajst-30235	3	22	the	the	DET
ajst-30235	3	23	change	change	NOUN
ajst-30235	3	24	of	of	ADP
ajst-30235	3	25	working	work	VERB
ajst-30235	3	26	conditions	condition	NOUN
ajst-30235	3	27	,	,	PUNCT
ajst-30235	3	28	the	the	DET
ajst-30235	3	29	signal	signal	NOUN
ajst-30235	3	30	features	feature	NOUN
ajst-30235	3	31	often	often	ADV
ajst-30235	3	32	appear	appear	VERB
ajst-30235	3	33	to	to	PART
ajst-30235	3	34	be	be	AUX
ajst-30235	3	35	mixed	mix	VERB
ajst-30235	3	36	,	,	PUNCT
ajst-30235	3	37	which	which	PRON
ajst-30235	3	38	brings	bring	VERB
ajst-30235	3	39	a	a	DET
ajst-30235	3	40	greater	great	ADJ
ajst-30235	3	41	challenge	challenge	NOUN
ajst-30235	3	42	to	to	ADP
ajst-30235	3	43	the	the	DET
ajst-30235	3	44	diagnosis	diagnosis	NOUN
ajst-30235	3	45	.	.	PUNCT
ajst-30235	4	1	in	in	ADP
ajst-30235	4	2	this	this	DET
ajst-30235	4	3	paper	paper	NOUN
ajst-30235	4	4	,	,	PUNCT
ajst-30235	4	5	a	a	DET
ajst-30235	4	6	bearing	bear	VERB
ajst-30235	4	7	fault	fault	NOUN
ajst-30235	4	8	diagnosis	diagnosis	NOUN
ajst-30235	4	9	method	method	NOUN
ajst-30235	4	10	based	base	VERB
ajst-30235	4	11	on	on	ADP
ajst-30235	4	12	squeezeand	squeezeand	NOUN
ajst-30235	4	13	-	-	PUNCT
ajst-30235	4	14	excitation	excitation	NOUN
ajst-30235	4	15	convolutional	convolutional	ADJ
ajst-30235	4	16	neural	neural	ADJ
ajst-30235	4	17	network	network	NOUN
ajst-30235	4	18	is	be	AUX
ajst-30235	4	19	proposed	propose	VERB
ajst-30235	4	20	.	.	PUNCT
ajst-30235	5	1	the	the	DET
ajst-30235	5	2	method	method	NOUN
ajst-30235	5	3	enhances	enhance	VERB
ajst-30235	5	4	the	the	DET
ajst-30235	5	5	network	network	NOUN
ajst-30235	5	6	's	's	PART
ajst-30235	5	7	focus	focus	NOUN
ajst-30235	5	8	on	on	ADP
ajst-30235	5	9	key	key	ADJ
ajst-30235	5	10	fault	fault	NOUN
ajst-30235	5	11	features	feature	NOUN
ajst-30235	5	12	by	by	ADP
ajst-30235	5	13	introducing	introduce	VERB
ajst-30235	5	14	the	the	DET
ajst-30235	5	15	se	se	PROPN
ajst-30235	5	16	module	module	NOUN
ajst-30235	5	17	to	to	PART
ajst-30235	5	18	adaptively	adaptively	ADV
ajst-30235	5	19	adjust	adjust	VERB
ajst-30235	5	20	the	the	DET
ajst-30235	5	21	weights	weight	NOUN
ajst-30235	5	22	of	of	ADP
ajst-30235	5	23	each	each	DET
ajst-30235	5	24	feature	feature	NOUN
ajst-30235	5	25	channel	channel	NOUN
ajst-30235	5	26	in	in	ADP
ajst-30235	5	27	the	the	DET
ajst-30235	5	28	convolutional	convolutional	ADJ
ajst-30235	5	29	network	network	NOUN
ajst-30235	5	30	,	,	PUNCT
ajst-30235	5	31	which	which	PRON
ajst-30235	5	32	optimizes	optimize	VERB
ajst-30235	5	33	the	the	DET
ajst-30235	5	34	feature	feature	NOUN
ajst-30235	5	35	extraction	extraction	NOUN
ajst-30235	5	36	ability	ability	NOUN
ajst-30235	5	37	of	of	ADP
ajst-30235	5	38	the	the	DET
ajst-30235	5	39	model	model	NOUN
ajst-30235	5	40	in	in	ADP
ajst-30235	5	41	complex	complex	ADJ
ajst-30235	5	42	vibration	vibration	NOUN
ajst-30235	5	43	signals	signal	NOUN
ajst-30235	5	44	.	.	PUNCT
ajst-30235	6	1	the	the	DET
ajst-30235	6	2	experimental	experimental	ADJ
ajst-30235	6	3	results	result	NOUN
ajst-30235	6	4	show	show	VERB
ajst-30235	6	5	that	that	SCONJ
ajst-30235	6	6	the	the	DET
ajst-30235	6	7	se	se	PROPN
ajst-30235	6	8	-	-	NOUN
ajst-30235	6	9	cnn	cnn	PROPN
ajst-30235	6	10	performs	perform	VERB
ajst-30235	6	11	superiorly	superiorly	ADV
ajst-30235	6	12	in	in	ADP
ajst-30235	6	13	terms	term	NOUN
ajst-30235	6	14	of	of	ADP
ajst-30235	6	15	precision	precision	NOUN
ajst-30235	6	16	rate	rate	NOUN
ajst-30235	6	17	,	,	PUNCT
ajst-30235	6	18	recall	recall	NOUN
ajst-30235	6	19	rate	rate	NOUN
ajst-30235	6	20	and	and	CCONJ
ajst-30235	6	21	f1	f1	NOUN
ajst-30235	6	22	-	-	PUNCT
ajst-30235	6	23	score	score	NOUN
ajst-30235	6	24	,	,	PUNCT
ajst-30235	6	25	especially	especially	ADV
ajst-30235	6	26	in	in	ADP
ajst-30235	6	27	the	the	DET
ajst-30235	6	28	case	case	NOUN
ajst-30235	6	29	of	of	ADP
ajst-30235	6	30	category	category	NOUN
ajst-30235	6	31	imbalance	imbalance	NOUN
ajst-30235	6	32	,	,	PUNCT
ajst-30235	6	33	the	the	DET
ajst-30235	6	34	se	se	PROPN
ajst-30235	6	35	-	-	NOUN
ajst-30235	6	36	cnn	cnn	PROPN
ajst-30235	6	37	has	have	VERB
ajst-30235	6	38	better	well	ADJ
ajst-30235	6	39	robustness	robustness	NOUN
ajst-30235	6	40	.	.	PUNCT
ajst-30235	7	1	keywords	keyword	NOUN
ajst-30235	7	2	:	:	PUNCT
ajst-30235	7	3	rolling	rolling	ADJ
ajst-30235	7	4	bearing	bearing	NOUN
ajst-30235	7	5	,	,	PUNCT
ajst-30235	7	6	fault	fault	NOUN
ajst-30235	7	7	diagnosis	diagnosis	NOUN
ajst-30235	7	8	,	,	PUNCT
ajst-30235	7	9	se	se	PROPN
ajst-30235	7	10	-	-	NOUN
ajst-30235	7	11	cnn	cnn	PROPN
ajst-30235	7	12	.	.	PUNCT
ajst-30235	8	1	1	1	X
ajst-30235	8	2	.	.	X
ajst-30235	8	3	introduction	introduction	NOUN
ajst-30235	8	4	in	in	ADP
ajst-30235	8	5	the	the	DET
ajst-30235	8	6	process	process	NOUN
ajst-30235	8	7	of	of	ADP
ajst-30235	8	8	industrial	industrial	ADJ
ajst-30235	8	9	equipment	equipment	NOUN
ajst-30235	8	10	operation	operation	NOUN
ajst-30235	8	11	,	,	PUNCT
ajst-30235	8	12	rolling	roll	VERB
ajst-30235	8	13	bearings	bearing	NOUN
ajst-30235	8	14	as	as	ADP
ajst-30235	8	15	the	the	DET
ajst-30235	8	16	core	core	ADJ
ajst-30235	8	17	components	component	NOUN
ajst-30235	8	18	of	of	ADP
ajst-30235	8	19	rotating	rotate	VERB
ajst-30235	8	20	machinery	machinery	NOUN
ajst-30235	8	21	,	,	PUNCT
ajst-30235	8	22	its	its	PRON
ajst-30235	8	23	health	health	NOUN
ajst-30235	8	24	status	status	NOUN
ajst-30235	8	25	directly	directly	ADV
ajst-30235	8	26	affects	affect	VERB
ajst-30235	8	27	the	the	DET
ajst-30235	8	28	operational	operational	ADJ
ajst-30235	8	29	efficiency	efficiency	NOUN
ajst-30235	8	30	and	and	CCONJ
ajst-30235	8	31	safety	safety	NOUN
ajst-30235	8	32	of	of	ADP
ajst-30235	8	33	the	the	DET
ajst-30235	8	34	equipment	equipment	NOUN
ajst-30235	8	35	.	.	PUNCT
ajst-30235	9	1	due	due	ADP
ajst-30235	9	2	to	to	ADP
ajst-30235	9	3	long	long	ADJ
ajst-30235	9	4	-	-	PUNCT
ajst-30235	9	5	term	term	NOUN
ajst-30235	9	6	exposure	exposure	NOUN
ajst-30235	9	7	to	to	ADP
ajst-30235	9	8	complex	complex	ADJ
ajst-30235	9	9	mechanical	mechanical	ADJ
ajst-30235	9	10	loads	load	NOUN
ajst-30235	9	11	,	,	PUNCT
ajst-30235	9	12	vibration	vibration	NOUN
ajst-30235	9	13	and	and	CCONJ
ajst-30235	9	14	environmental	environmental	ADJ
ajst-30235	9	15	factors	factor	NOUN
ajst-30235	9	16	,	,	PUNCT
ajst-30235	9	17	bearings	bearing	NOUN
ajst-30235	9	18	are	be	AUX
ajst-30235	9	19	prone	prone	ADJ
ajst-30235	9	20	to	to	ADP
ajst-30235	9	21	fatigue	fatigue	NOUN
ajst-30235	9	22	damage	damage	NOUN
ajst-30235	9	23	,	,	PUNCT
ajst-30235	9	24	wear	wear	VERB
ajst-30235	9	25	and	and	CCONJ
ajst-30235	9	26	even	even	ADV
ajst-30235	9	27	failure	failure	NOUN
ajst-30235	9	28	.	.	PUNCT
ajst-30235	10	1	therefore	therefore	ADV
ajst-30235	10	2	,	,	PUNCT
ajst-30235	10	3	the	the	DET
ajst-30235	10	4	accurate	accurate	ADJ
ajst-30235	10	5	identification	identification	NOUN
ajst-30235	10	6	of	of	ADP
ajst-30235	10	7	bearing	bear	VERB
ajst-30235	10	8	health	health	NOUN
ajst-30235	10	9	condition	condition	NOUN
ajst-30235	10	10	,	,	PUNCT
ajst-30235	10	11	which	which	PRON
ajst-30235	10	12	provides	provide	VERB
ajst-30235	10	13	the	the	DET
ajst-30235	10	14	basis	basis	NOUN
ajst-30235	10	15	for	for	ADP
ajst-30235	10	16	maintenance	maintenance	NOUN
ajst-30235	10	17	decision	decision	NOUN
ajst-30235	10	18	-	-	PUNCT
ajst-30235	10	19	making	making	NOUN
ajst-30235	10	20	,	,	PUNCT
ajst-30235	10	21	has	have	AUX
ajst-30235	10	22	become	become	VERB
ajst-30235	10	23	an	an	DET
ajst-30235	10	24	important	important	ADJ
ajst-30235	10	25	task	task	NOUN
ajst-30235	10	26	to	to	PART
ajst-30235	10	27	ensure	ensure	VERB
ajst-30235	10	28	the	the	DET
ajst-30235	10	29	smooth	smooth	ADJ
ajst-30235	10	30	operation	operation	NOUN
ajst-30235	10	31	of	of	ADP
ajst-30235	10	32	equipment	equipment	NOUN
ajst-30235	10	33	.	.	PUNCT
ajst-30235	11	1	traditional	traditional	ADJ
ajst-30235	11	2	intelligent	intelligent	ADJ
ajst-30235	11	3	diagnosis	diagnosis	NOUN
ajst-30235	11	4	methods	method	NOUN
ajst-30235	11	5	for	for	ADP
ajst-30235	11	6	bearing	bear	VERB
ajst-30235	11	7	faults	fault	NOUN
ajst-30235	11	8	generally	generally	ADV
ajst-30235	11	9	require	require	VERB
ajst-30235	11	10	the	the	DET
ajst-30235	11	11	help	help	NOUN
ajst-30235	11	12	of	of	ADP
ajst-30235	11	13	fast	fast	ADJ
ajst-30235	11	14	fourier	fourier	NOUN
ajst-30235	11	15	transform	transform	NOUN
ajst-30235	11	16	,	,	PUNCT
ajst-30235	11	17	wavelet	wavelet	NOUN
ajst-30235	11	18	transform	transform	NOUN
ajst-30235	11	19	and	and	CCONJ
ajst-30235	11	20	empirical	empirical	ADJ
ajst-30235	11	21	modal	modal	NOUN
ajst-30235	11	22	decomposition[1	decomposition[1	PROPN
ajst-30235	11	23	-	-	PUNCT
ajst-30235	11	24	3],the	3],the	DET
ajst-30235	11	25	acquired	acquire	VERB
ajst-30235	11	26	signals	signal	NOUN
ajst-30235	11	27	are	be	AUX
ajst-30235	11	28	processed	process	VERB
ajst-30235	11	29	,	,	PUNCT
ajst-30235	11	30	the	the	DET
ajst-30235	11	31	features	feature	NOUN
ajst-30235	11	32	are	be	AUX
ajst-30235	11	33	artificially	artificially	ADV
ajst-30235	11	34	designed	design	VERB
ajst-30235	11	35	and	and	CCONJ
ajst-30235	11	36	extracted	extract	VERB
ajst-30235	11	37	by	by	ADP
ajst-30235	11	38	combining	combine	VERB
ajst-30235	11	39	expert	expert	ADJ
ajst-30235	11	40	experience	experience	NOUN
ajst-30235	11	41	,	,	PUNCT
ajst-30235	11	42	and	and	CCONJ
ajst-30235	11	43	finally	finally	ADV
ajst-30235	11	44	the	the	DET
ajst-30235	11	45	fault	fault	NOUN
ajst-30235	11	46	identification	identification	NOUN
ajst-30235	11	47	is	be	AUX
ajst-30235	11	48	realized	realize	VERB
ajst-30235	11	49	by	by	ADP
ajst-30235	11	50	a	a	DET
ajst-30235	11	51	back	back	ADJ
ajst-30235	11	52	-	-	PUNCT
ajst-30235	11	53	end	end	NOUN
ajst-30235	11	54	classifier	classifier	NOUN
ajst-30235	11	55	,	,	PUNCT
ajst-30235	11	56	such	such	ADJ
ajst-30235	11	57	as	as	ADP
ajst-30235	11	58	artificial	artificial	ADJ
ajst-30235	11	59	neural	neural	ADJ
ajst-30235	11	60	network[4	network[4	NOUN
ajst-30235	11	61	]	]	X
ajst-30235	11	62	,	,	PUNCT
ajst-30235	11	63	svm[5	svm[5	NOUN
ajst-30235	11	64	]	]	PUNCT
ajst-30235	11	65	,	,	PUNCT
ajst-30235	11	66	and	and	CCONJ
ajst-30235	11	67	rf[6	rf[6	PROPN
ajst-30235	11	68	]	]	X
ajst-30235	11	69	,	,	PUNCT
ajst-30235	11	70	etc	etc	X
ajst-30235	11	71	.	.	X
ajst-30235	12	1	however	however	ADV
ajst-30235	12	2	,	,	PUNCT
ajst-30235	12	3	such	such	ADJ
ajst-30235	12	4	methods	method	NOUN
ajst-30235	12	5	have	have	VERB
ajst-30235	12	6	the	the	DET
ajst-30235	12	7	defects	defect	NOUN
ajst-30235	12	8	of	of	ADP
ajst-30235	12	9	relying	rely	VERB
ajst-30235	12	10	on	on	ADP
ajst-30235	12	11	expert	expert	ADJ
ajst-30235	12	12	experience	experience	NOUN
ajst-30235	12	13	,	,	PUNCT
ajst-30235	12	14	cumbersome	cumbersome	ADJ
ajst-30235	12	15	procedure	procedure	NOUN
ajst-30235	12	16	,	,	PUNCT
ajst-30235	12	17	and	and	CCONJ
ajst-30235	12	18	poor	poor	ADJ
ajst-30235	12	19	nonlinear	nonlinear	ADJ
ajst-30235	12	20	fitting	fitting	ADJ
ajst-30235	12	21	ability	ability	NOUN
ajst-30235	12	22	.	.	PUNCT
ajst-30235	13	1	however	however	ADV
ajst-30235	13	2	,	,	PUNCT
ajst-30235	13	3	such	such	ADJ
ajst-30235	13	4	methods	method	NOUN
ajst-30235	13	5	have	have	VERB
ajst-30235	13	6	the	the	DET
ajst-30235	13	7	defects	defect	NOUN
ajst-30235	13	8	of	of	ADP
ajst-30235	13	9	relying	rely	VERB
ajst-30235	13	10	on	on	ADP
ajst-30235	13	11	experts	expert	NOUN
ajst-30235	13	12	'	'	PART
ajst-30235	13	13	experience	experience	NOUN
ajst-30235	13	14	,	,	PUNCT
ajst-30235	13	15	cumbersome	cumbersome	ADJ
ajst-30235	13	16	procedures	procedure	NOUN
ajst-30235	13	17	and	and	CCONJ
ajst-30235	13	18	poor	poor	ADJ
ajst-30235	13	19	nonlinear	nonlinear	ADJ
ajst-30235	13	20	fitting	fitting	ADJ
ajst-30235	13	21	ability	ability	NOUN
ajst-30235	13	22	of	of	ADP
ajst-30235	13	23	shallow	shallow	ADJ
ajst-30235	13	24	classifiers[7	classifiers[7	NOUN
ajst-30235	13	25	-	-	PUNCT
ajst-30235	13	26	8	8	NUM
ajst-30235	13	27	]	]	PUNCT
ajst-30235	13	28	.	.	PUNCT
ajst-30235	14	1	the	the	DET
ajst-30235	14	2	deep	deep	ADJ
ajst-30235	14	3	neural	neural	ADJ
ajst-30235	14	4	networks	network	NOUN
ajst-30235	14	5	that	that	PRON
ajst-30235	14	6	have	have	AUX
ajst-30235	14	7	emerged	emerge	VERB
ajst-30235	14	8	in	in	ADP
ajst-30235	14	9	recent	recent	ADJ
ajst-30235	14	10	years	year	NOUN
ajst-30235	14	11	have	have	VERB
ajst-30235	14	12	a	a	DET
ajst-30235	14	13	strong	strong	ADJ
ajst-30235	14	14	nonlinear	nonlinear	ADJ
ajst-30235	14	15	ability	ability	NOUN
ajst-30235	14	16	to	to	PART
ajst-30235	14	17	automatically	automatically	ADV
ajst-30235	14	18	learn	learn	VERB
ajst-30235	14	19	deep	deep	ADJ
ajst-30235	14	20	feature	feature	NOUN
ajst-30235	14	21	representations	representation	NOUN
ajst-30235	14	22	from	from	ADP
ajst-30235	14	23	data	datum	NOUN
ajst-30235	14	24	,	,	PUNCT
ajst-30235	14	25	making	make	VERB
ajst-30235	14	26	up	up	ADP
ajst-30235	14	27	for	for	ADP
ajst-30235	14	28	the	the	DET
ajst-30235	14	29	shortcomings	shortcoming	NOUN
ajst-30235	14	30	of	of	ADP
ajst-30235	14	31	traditional	traditional	ADJ
ajst-30235	14	32	methods	method	NOUN
ajst-30235	14	33	of	of	ADP
ajst-30235	14	34	intelligent	intelligent	ADJ
ajst-30235	14	35	diagnosis	diagnosis	NOUN
ajst-30235	14	36	of	of	ADP
ajst-30235	14	37	bearing	bear	VERB
ajst-30235	14	38	faults	fault	NOUN
ajst-30235	14	39	and	and	CCONJ
ajst-30235	14	40	bringing	bring	VERB
ajst-30235	14	41	new	new	ADJ
ajst-30235	14	42	solution	solution	NOUN
ajst-30235	14	43	ideas.janssens	ideas.janssens	ADP
ajst-30235	14	44	et	et	NOUN
ajst-30235	14	45	al[9	al[9	NOUN
ajst-30235	14	46	]	]	PUNCT
ajst-30235	14	47	introduced	introduce	VERB
ajst-30235	14	48	convolutional	convolutional	ADJ
ajst-30235	14	49	neural	neural	ADJ
ajst-30235	14	50	networks	network	NOUN
ajst-30235	14	51	into	into	ADP
ajst-30235	14	52	the	the	DET
ajst-30235	14	53	field	field	NOUN
ajst-30235	14	54	of	of	ADP
ajst-30235	14	55	fault	fault	NOUN
ajst-30235	14	56	diagnosis	diagnosis	NOUN
ajst-30235	14	57	,	,	PUNCT
ajst-30235	14	58	where	where	SCONJ
ajst-30235	14	59	the	the	DET
ajst-30235	14	60	raw	raw	ADJ
ajst-30235	14	61	signals	signal	NOUN
ajst-30235	14	62	are	be	AUX
ajst-30235	14	63	processed	process	VERB
ajst-30235	14	64	by	by	ADP
ajst-30235	14	65	discrete	discrete	ADJ
ajst-30235	14	66	fourier	fourier	NOUN
ajst-30235	14	67	transform	transform	NOUN
ajst-30235	14	68	and	and	CCONJ
ajst-30235	14	69	then	then	ADV
ajst-30235	14	70	used	use	VERB
ajst-30235	14	71	as	as	ADP
ajst-30235	14	72	inputs	input	NOUN
ajst-30235	14	73	to	to	ADP
ajst-30235	14	74	a	a	DET
ajst-30235	14	75	cnn	cnn	PROPN
ajst-30235	14	76	model	model	NOUN
ajst-30235	14	77	for	for	ADP
ajst-30235	14	78	fault	fault	NOUN
ajst-30235	14	79	identification.shebo	identification.shebo	NUM
ajst-30235	14	80	et	et	NOUN
ajst-30235	14	81	al[10	al[10	NUM
ajst-30235	14	82	]	]	PUNCT
ajst-30235	14	83	proposed	propose	VERB
ajst-30235	14	84	a	a	DET
ajst-30235	14	85	fault	fault	NOUN
ajst-30235	14	86	diagnosis	diagnosis	NOUN
ajst-30235	14	87	method	method	NOUN
ajst-30235	14	88	based	base	VERB
ajst-30235	14	89	on	on	ADP
ajst-30235	14	90	deep	deep	ADJ
ajst-30235	14	91	convolutional	convolutional	ADJ
ajst-30235	14	92	variational	variational	ADJ
ajst-30235	14	93	self	self	NOUN
ajst-30235	14	94	-	-	PUNCT
ajst-30235	14	95	coding	code	VERB
ajst-30235	14	96	network(dcvaen	network(dcvaen	NOUN
ajst-30235	14	97	)	)	PUNCT
ajst-30235	14	98	,	,	PUNCT
ajst-30235	14	99	which	which	PRON
ajst-30235	14	100	directly	directly	ADV
ajst-30235	14	101	utilizes	utilize	VERB
ajst-30235	14	102	the	the	DET
ajst-30235	14	103	spectral	spectral	ADJ
ajst-30235	14	104	information	information	NOUN
ajst-30235	14	105	of	of	ADP
ajst-30235	14	106	vibration	vibration	NOUN
ajst-30235	14	107	signals	signal	NOUN
ajst-30235	14	108	as	as	ADP
ajst-30235	14	109	training	training	NOUN
ajst-30235	14	110	data	datum	NOUN
ajst-30235	14	111	for	for	ADP
ajst-30235	14	112	fault	fault	NOUN
ajst-30235	14	113	diagnosis	diagnosis	NOUN
ajst-30235	14	114	.	.	PUNCT
ajst-30235	15	1	however	however	ADV
ajst-30235	15	2	,	,	PUNCT
ajst-30235	15	3	the	the	DET
ajst-30235	15	4	theory	theory	NOUN
ajst-30235	15	5	has	have	AUX
ajst-30235	15	6	achieved	achieve	VERB
ajst-30235	15	7	great	great	ADJ
ajst-30235	15	8	success	success	NOUN
ajst-30235	15	9	,	,	PUNCT
ajst-30235	15	10	but	but	CCONJ
ajst-30235	15	11	in	in	ADP
ajst-30235	15	12	practical	practical	ADJ
ajst-30235	15	13	applications	application	NOUN
ajst-30235	15	14	,	,	PUNCT
ajst-30235	15	15	bearings	bearing	NOUN
ajst-30235	15	16	in	in	ADP
ajst-30235	15	17	the	the	DET
ajst-30235	15	18	load	load	NOUN
ajst-30235	15	19	,	,	PUNCT
ajst-30235	15	20	speed	speed	NOUN
ajst-30235	15	21	and	and	CCONJ
ajst-30235	15	22	other	other	ADJ
ajst-30235	15	23	conditions	condition	NOUN
ajst-30235	15	24	of	of	ADP
ajst-30235	15	25	the	the	DET
ajst-30235	15	26	working	work	VERB
ajst-30235	15	27	conditions	condition	NOUN
ajst-30235	15	28	change	change	VERB
ajst-30235	15	29	conditions	condition	NOUN
ajst-30235	15	30	,	,	PUNCT
ajst-30235	15	31	different	different	ADJ
ajst-30235	15	32	changes	change	NOUN
ajst-30235	15	33	in	in	ADP
ajst-30235	15	34	working	work	VERB
ajst-30235	15	35	conditions	condition	NOUN
ajst-30235	15	36	will	will	AUX
ajst-30235	15	37	cause	cause	VERB
ajst-30235	15	38	non	non	ADJ
ajst-30235	15	39	-	-	ADJ
ajst-30235	15	40	linear	linear	ADJ
ajst-30235	15	41	changes	change	NOUN
ajst-30235	15	42	in	in	ADP
ajst-30235	15	43	vibration	vibration	NOUN
ajst-30235	15	44	signals	signal	NOUN
ajst-30235	15	45	,	,	PUNCT
ajst-30235	15	46	resulting	result	VERB
ajst-30235	15	47	in	in	ADP
ajst-30235	15	48	different	different	ADJ
ajst-30235	15	49	fault	fault	NOUN
ajst-30235	15	50	location	location	NOUN
ajst-30235	15	51	,	,	PUNCT
ajst-30235	15	52	different	different	ADJ
ajst-30235	15	53	severity	severity	NOUN
ajst-30235	15	54	of	of	ADP
ajst-30235	15	55	the	the	DET
ajst-30235	15	56	vibration	vibration	NOUN
ajst-30235	15	57	signals	signal	NOUN
ajst-30235	15	58	appeared	appear	VERB
ajst-30235	15	59	in	in	ADP
ajst-30235	15	60	the	the	DET
ajst-30235	15	61	overlap	overlap	NOUN
ajst-30235	15	62	,	,	PUNCT
ajst-30235	15	63	which	which	PRON
ajst-30235	15	64	in	in	ADP
ajst-30235	15	65	turn	turn	NOUN
ajst-30235	15	66	increases	increase	VERB
ajst-30235	15	67	the	the	DET
ajst-30235	15	68	difficulty	difficulty	NOUN
ajst-30235	15	69	of	of	ADP
ajst-30235	15	70	the	the	DET
ajst-30235	15	71	bearing	bear	VERB
ajst-30235	15	72	fault	fault	NOUN
ajst-30235	15	73	diagnosis	diagnosis	NOUN
ajst-30235	15	74	.	.	PUNCT
ajst-30235	16	1	to	to	PART
ajst-30235	16	2	address	address	VERB
ajst-30235	16	3	the	the	DET
ajst-30235	16	4	above	above	ADJ
ajst-30235	16	5	problems	problem	NOUN
ajst-30235	16	6	,	,	PUNCT
ajst-30235	16	7	this	this	DET
ajst-30235	16	8	paper	paper	NOUN
ajst-30235	16	9	proposes	propose	VERB
ajst-30235	16	10	a	a	DET
ajst-30235	16	11	bearing	bearing	NOUN
ajst-30235	16	12	fault	fault	NOUN
ajst-30235	16	13	diagnosis	diagnosis	NOUN
ajst-30235	16	14	method	method	NOUN
ajst-30235	16	15	based	base	VERB
ajst-30235	16	16	on	on	ADP
ajst-30235	16	17	squeeze	squeeze	NOUN
ajst-30235	16	18	-	-	PUNCT
ajst-30235	16	19	andexcitation	andexcitation	NOUN
ajst-30235	16	20	convolutional	convolutional	ADJ
ajst-30235	16	21	neural	neural	ADJ
ajst-30235	16	22	network.the	network.the	DET
ajst-30235	16	23	se	se	PROPN
ajst-30235	16	24	module	module	NOUN
ajst-30235	16	25	enhances	enhance	VERB
ajst-30235	16	26	the	the	DET
ajst-30235	16	27	expression	expression	NOUN
ajst-30235	16	28	of	of	ADP
ajst-30235	16	29	key	key	ADJ
ajst-30235	16	30	features	feature	NOUN
ajst-30235	16	31	by	by	ADP
ajst-30235	16	32	adaptively	adaptively	ADV
ajst-30235	16	33	adjusting	adjust	VERB
ajst-30235	16	34	the	the	DET
ajst-30235	16	35	feature	feature	NOUN
ajst-30235	16	36	weights	weight	NOUN
ajst-30235	16	37	between	between	ADP
ajst-30235	16	38	channels	channel	NOUN
ajst-30235	16	39	,	,	PUNCT
ajst-30235	16	40	and	and	CCONJ
ajst-30235	16	41	the	the	DET
ajst-30235	16	42	cnn	cnn	NOUN
ajst-30235	16	43	targetedly	targetedly	ADV
ajst-30235	16	44	adjusts	adjust	VERB
ajst-30235	16	45	the	the	DET
ajst-30235	16	46	feature	feature	NOUN
ajst-30235	16	47	channel	channel	NOUN
ajst-30235	16	48	weights	weight	NOUN
ajst-30235	16	49	of	of	ADP
ajst-30235	16	50	the	the	DET
ajst-30235	16	51	convolutional	convolutional	ADJ
ajst-30235	16	52	layer	layer	NOUN
ajst-30235	16	53	to	to	PART
ajst-30235	16	54	increase	increase	VERB
ajst-30235	16	55	the	the	DET
ajst-30235	16	56	weights	weight	NOUN
ajst-30235	16	57	of	of	ADP
ajst-30235	16	58	special	special	ADJ
ajst-30235	16	59	channels	channel	NOUN
ajst-30235	16	60	that	that	PRON
ajst-30235	16	61	contain	contain	VERB
ajst-30235	16	62	fault	fault	NOUN
ajst-30235	16	63	information	information	NOUN
ajst-30235	16	64	and	and	CCONJ
ajst-30235	16	65	cut	cut	VERB
ajst-30235	16	66	down	down	ADP
ajst-30235	16	67	the	the	DET
ajst-30235	16	68	useless	useless	ADJ
ajst-30235	16	69	feature	feature	NOUN
ajst-30235	16	70	channels	channel	NOUN
ajst-30235	16	71	.	.	PUNCT
ajst-30235	17	1	2	2	X
ajst-30235	17	2	.	.	X
ajst-30235	17	3	theoretical	theoretical	ADJ
ajst-30235	17	4	foundations	foundation	NOUN
ajst-30235	17	5	2.1	2.1	NUM
ajst-30235	17	6	.	.	PUNCT
ajst-30235	17	7	squeeze	squeeze	NOUN
ajst-30235	17	8	-	-	PUNCT
ajst-30235	17	9	and	and	CCONJ
ajst-30235	17	10	-	-	PUNCT
ajst-30235	17	11	excitation	excitation	NOUN
ajst-30235	17	12	networks	network	NOUN
ajst-30235	17	13	se	se	X
ajst-30235	17	14	is	be	AUX
ajst-30235	17	15	a	a	DET
ajst-30235	17	16	lightweight	lightweight	ADJ
ajst-30235	17	17	attentional	attentional	ADJ
ajst-30235	17	18	mechanism	mechanism	NOUN
ajst-30235	17	19	focusing	focus	VERB
ajst-30235	17	20	on	on	ADP
ajst-30235	17	21	channel	channel	NOUN
ajst-30235	17	22	information	information	NOUN
ajst-30235	17	23	,	,	PUNCT
ajst-30235	17	24	which	which	PRON
ajst-30235	17	25	is	be	AUX
ajst-30235	17	26	added	add	VERB
ajst-30235	17	27	to	to	ADP
ajst-30235	17	28	existing	exist	VERB
ajst-30235	17	29	neural	neural	ADJ
ajst-30235	17	30	networks	network	NOUN
ajst-30235	17	31	to	to	PART
ajst-30235	17	32	improve	improve	VERB
ajst-30235	17	33	the	the	DET
ajst-30235	17	34	model	model	NOUN
ajst-30235	17	35	performance	performance	NOUN
ajst-30235	17	36	with	with	ADP
ajst-30235	17	37	only	only	ADV
ajst-30235	17	38	a	a	DET
ajst-30235	17	39	small	small	ADJ
ajst-30235	17	40	increase	increase	NOUN
ajst-30235	17	41	in	in	ADP
ajst-30235	17	42	computational	computational	ADJ
ajst-30235	17	43	effort	effort	NOUN
ajst-30235	17	44	[	[	X
ajst-30235	17	45	11	11	NUM
ajst-30235	17	46	-	-	SYM
ajst-30235	17	47	12].se	12].se	NUM
ajst-30235	17	48	networks	network	NOUN
ajst-30235	17	49	are	be	AUX
ajst-30235	17	50	able	able	ADJ
ajst-30235	17	51	to	to	PART
ajst-30235	17	52	recalibrate	recalibrate	VERB
ajst-30235	17	53	the	the	DET
ajst-30235	17	54	channel	channel	NOUN
ajst-30235	17	55	response	response	NOUN
ajst-30235	17	56	to	to	ADP
ajst-30235	17	57	features	feature	NOUN
ajst-30235	17	58	through	through	ADP
ajst-30235	17	59	the	the	DET
ajst-30235	17	60	interdependencies	interdependency	NOUN
ajst-30235	17	61	between	between	ADP
ajst-30235	17	62	channels	channel	NOUN
ajst-30235	17	63	,	,	PUNCT
ajst-30235	17	64	enhancing	enhance	VERB
ajst-30235	17	65	the	the	DET
ajst-30235	17	66	network	network	NOUN
ajst-30235	17	67	's	's	PART
ajst-30235	17	68	representational	representational	ADJ
ajst-30235	17	69	capabilities	capability	NOUN
ajst-30235	17	70	.	.	PUNCT
ajst-30235	18	1	the	the	DET
ajst-30235	18	2	se	se	PROPN
ajst-30235	18	3	network	network	PROPN
ajst-30235	18	4	consists	consist	VERB
ajst-30235	18	5	of	of	ADP
ajst-30235	18	6	three	three	NUM
ajst-30235	18	7	parts	part	NOUN
ajst-30235	18	8	,	,	PUNCT
ajst-30235	18	9	the	the	DET
ajst-30235	18	10	squeeze	squeeze	NOUN
ajst-30235	18	11	,	,	PUNCT
ajst-30235	18	12	the	the	DET
ajst-30235	18	13	excitation	excitation	NOUN
ajst-30235	18	14	and	and	CCONJ
ajst-30235	18	15	the	the	DET
ajst-30235	18	16	scale	scale	NOUN
ajst-30235	18	17	and	and	CCONJ
ajst-30235	18	18	multiply	multiply	NOUN
ajst-30235	18	19	feature	feature	NOUN
ajst-30235	18	20	fusion	fusion	NOUN
ajst-30235	18	21	operation	operation	NOUN
ajst-30235	18	22	.	.	PUNCT
ajst-30235	19	1	where	where	SCONJ
ajst-30235	19	2	the	the	DET
ajst-30235	19	3	global	global	ADJ
ajst-30235	19	4	average	average	ADJ
ajst-30235	19	5	pooling	pooling	NOUN
ajst-30235	19	6	of	of	ADP
ajst-30235	19	7	squeeze	squeeze	NOUN
ajst-30235	19	8	is	be	AUX
ajst-30235	19	9	a	a	DET
ajst-30235	19	10	channel	channel	NOUN
ajst-30235	19	11	statistic	statistic	NOUN
ajst-30235	19	12	generated	generate	VERB
ajst-30235	19	13	by	by	ADP
ajst-30235	19	14	equation	equation	NOUN
ajst-30235	19	15	(	(	PUNCT
ajst-30235	19	16	1	1	NUM
ajst-30235	19	17	)	)	PUNCT
ajst-30235	19	18	that	that	PRON
ajst-30235	19	19	encodes	encode	VERB
ajst-30235	19	20	the	the	DET
ajst-30235	19	21	spatial	spatial	ADJ
ajst-30235	19	22	features	feature	NOUN
ajst-30235	19	23	on	on	ADP
ajst-30235	19	24	a	a	DET
ajst-30235	19	25	channel	channel	NOUN
ajst-30235	19	26	into	into	ADP
ajst-30235	19	27	a	a	DET
ajst-30235	19	28	global	global	ADJ
ajst-30235	19	29	feature	feature	NOUN
ajst-30235	19	30	that	that	PRON
ajst-30235	19	31	preserves	preserve	VERB
ajst-30235	19	32	the	the	DET
ajst-30235	19	33	overall	overall	ADJ
ajst-30235	19	34	semantic	semantic	ADJ
ajst-30235	19	35	information	information	NOUN
ajst-30235	19	36	.	.	PUNCT
ajst-30235	20	1	sq	sq	INTJ
ajst-30235	20	2	1	1	NUM
ajst-30235	20	3	1	1	NUM
ajst-30235	20	4	1	1	NUM
ajst-30235	20	5	z	z	NOUN
ajst-30235	20	6	(	(	PUNCT
ajst-30235	20	7	)	)	PUNCT
ajst-30235	20	8	(	(	PUNCT
ajst-30235	20	9	,	,	PUNCT
ajst-30235	20	10	)	)	PUNCT
ajst-30235	20	11	w	w	PROPN
ajst-30235	20	12	h	h	NOUN
ajst-30235	21	1	w	w	NOUN
ajst-30235	21	2	c	c	NOUN
ajst-30235	21	3	c	c	NOUN
ajst-30235	22	1	c	c	NOUN
ajst-30235	23	1	i	i	PRON
ajst-30235	23	2	j	j	NOUN
ajst-30235	24	1	f	f	X
ajst-30235	24	2	u	u	PROPN
ajst-30235	24	3	u	u	VERB
ajst-30235	24	4	i	i	NOUN
ajst-30235	24	5	j	j	PROPN
ajst-30235	25	1	h	h	NOUN
ajst-30235	26	1			NOUN
ajst-30235	27	1			PRON
ajst-30235	28	1			PRON
ajst-30235	29	1			PROPN
ajst-30235	29	2			NOUN
ajst-30235	29	3			PRON
ajst-30235	29	4	(	(	PUNCT
ajst-30235	29	5	1	1	X
ajst-30235	29	6	)	)	PUNCT
ajst-30235	29	7	where	where	SCONJ
ajst-30235	29	8	u	u	PROPN
ajst-30235	29	9	i	i	PROPN
ajst-30235	29	10	,	,	PUNCT
ajst-30235	29	11	j	j	PROPN
ajst-30235	29	12	is	be	AUX
ajst-30235	29	13	the	the	DET
ajst-30235	29	14	data	datum	NOUN
ajst-30235	29	15	at	at	ADP
ajst-30235	29	16	position	position	NOUN
ajst-30235	29	17	(	(	PUNCT
ajst-30235	29	18	i	i	PROPN
ajst-30235	29	19	,	,	PUNCT
ajst-30235	29	20	j	j	PROPN
ajst-30235	29	21	)	)	PUNCT
ajst-30235	29	22	in	in	ADP
ajst-30235	29	23	the	the	DET
ajst-30235	29	24	cth	cth	PROPN
ajst-30235	29	25	channel，z	channel，z	PROPN
ajst-30235	29	26	is	be	AUX
ajst-30235	29	27	the	the	DET
ajst-30235	29	28	response	response	NOUN
ajst-30235	29	29	data	datum	NOUN
ajst-30235	29	30	of	of	ADP
ajst-30235	29	31	the	the	DET
ajst-30235	29	32	compressed	compressed	ADJ
ajst-30235	29	33	part	part	NOUN
ajst-30235	29	34	in	in	ADP
ajst-30235	29	35	the	the	DET
ajst-30235	29	36	372	372	NUM
ajst-30235	29	37	cth	cth	PROPN
ajst-30235	29	38	channel；h	channel；h	PROPN
ajst-30235	29	39	,	,	PUNCT
ajst-30235	29	40	w	w	PROPN
ajst-30235	29	41	are	be	AUX
ajst-30235	29	42	the	the	DET
ajst-30235	29	43	length	length	NOUN
ajst-30235	29	44	and	and	CCONJ
ajst-30235	29	45	width	width	NOUN
ajst-30235	29	46	of	of	ADP
ajst-30235	29	47	the	the	DET
ajst-30235	29	48	data	datum	NOUN
ajst-30235	29	49	,	,	PUNCT
ajst-30235	29	50	respectively	respectively	ADV
ajst-30235	29	51	.	.	PUNCT
ajst-30235	30	1	the	the	DET
ajst-30235	30	2	goal	goal	NOUN
ajst-30235	30	3	of	of	ADP
ajst-30235	30	4	the	the	DET
ajst-30235	30	5	excitation	excitation	NOUN
ajst-30235	30	6	is	be	AUX
ajst-30235	30	7	to	to	PART
ajst-30235	30	8	fully	fully	ADV
ajst-30235	30	9	capture	capture	VERB
ajst-30235	30	10	the	the	DET
ajst-30235	30	11	dependencies	dependency	NOUN
ajst-30235	30	12	on	on	ADP
ajst-30235	30	13	channel	channel	NOUN
ajst-30235	30	14	dimensions	dimension	NOUN
ajst-30235	30	15	and	and	CCONJ
ajst-30235	30	16	parameterize	parameterize	VERB
ajst-30235	30	17	the	the	DET
ajst-30235	30	18	attention	attention	NOUN
ajst-30235	30	19	mechanism	mechanism	NOUN
ajst-30235	30	20	through	through	ADP
ajst-30235	30	21	two	two	NUM
ajst-30235	30	22	fully	fully	ADV
ajst-30235	30	23	connected	connected	ADJ
ajst-30235	30	24	layers	layer	NOUN
ajst-30235	30	25	.	.	PUNCT
ajst-30235	31	1	by	by	ADP
ajst-30235	31	2	connecting	connect	VERB
ajst-30235	31	3	the	the	DET
ajst-30235	31	4	two	two	NUM
ajst-30235	31	5	fully	fully	ADV
ajst-30235	31	6	-	-	PUNCT
ajst-30235	31	7	connected	connect	VERB
ajst-30235	31	8	layers	layer	NOUN
ajst-30235	31	9	in	in	ADP
ajst-30235	31	10	series	series	NOUN
ajst-30235	31	11	,	,	PUNCT
ajst-30235	31	12	not	not	PART
ajst-30235	31	13	only	only	ADV
ajst-30235	31	14	is	be	AUX
ajst-30235	31	15	it	it	PRON
ajst-30235	31	16	possible	possible	ADJ
ajst-30235	31	17	to	to	PART
ajst-30235	31	18	achieve	achieve	VERB
ajst-30235	31	19	a	a	DET
ajst-30235	31	20	nonlinear	nonlinear	ADJ
ajst-30235	31	21	mapping	mapping	NOUN
ajst-30235	31	22	that	that	PRON
ajst-30235	31	23	enhances	enhance	VERB
ajst-30235	31	24	or	or	CCONJ
ajst-30235	31	25	suppresses	suppress	VERB
ajst-30235	31	26	the	the	DET
ajst-30235	31	27	feature	feature	NOUN
ajst-30235	31	28	representation	representation	NOUN
ajst-30235	31	29	of	of	ADP
ajst-30235	31	30	a	a	DET
ajst-30235	31	31	particular	particular	ADJ
ajst-30235	31	32	channel	channel	NOUN
ajst-30235	31	33	,	,	PUNCT
ajst-30235	31	34	but	but	CCONJ
ajst-30235	31	35	it	it	PRON
ajst-30235	31	36	is	be	AUX
ajst-30235	31	37	also	also	ADV
ajst-30235	31	38	possible	possible	ADJ
ajst-30235	31	39	to	to	PART
ajst-30235	31	40	optimize	optimize	VERB
ajst-30235	31	41	the	the	DET
ajst-30235	31	42	parameter	parameter	NOUN
ajst-30235	31	43	scales	scale	NOUN
ajst-30235	31	44	of	of	ADP
ajst-30235	31	45	the	the	DET
ajst-30235	31	46	model	model	NOUN
ajst-30235	31	47	and	and	CCONJ
ajst-30235	31	48	improve	improve	VERB
ajst-30235	31	49	the	the	DET
ajst-30235	31	50	ability	ability	NOUN
ajst-30235	31	51	to	to	PART
ajst-30235	31	52	fit	fit	VERB
ajst-30235	31	53	inter	inter	ADJ
ajst-30235	31	54	-	-	ADJ
ajst-30235	31	55	channel	channel	NOUN
ajst-30235	31	56	correlations	correlation	NOUN
ajst-30235	31	57	.	.	PUNCT
ajst-30235	32	1	the	the	DET
ajst-30235	32	2	realization	realization	NOUN
ajst-30235	32	3	of	of	ADP
ajst-30235	32	4	this	this	DET
ajst-30235	32	5	excitation	excitation	NOUN
ajst-30235	32	6	operation	operation	NOUN
ajst-30235	32	7	can	can	AUX
ajst-30235	32	8	be	be	AUX
ajst-30235	32	9	expressed	express	VERB
ajst-30235	32	10	by	by	ADP
ajst-30235	32	11	equation	equation	NOUN
ajst-30235	32	12	(	(	PUNCT
ajst-30235	32	13	2	2	NUM
ajst-30235	32	14	)	)	PUNCT
ajst-30235	32	15	.	.	PUNCT
ajst-30235	33	1	ex	ex	X
ajst-30235	33	2	2	2	NUM
ajst-30235	33	3	1	1	NUM
ajst-30235	33	4	(	(	PUNCT
ajst-30235	33	5	,	,	PUNCT
ajst-30235	33	6	)	)	PUNCT
ajst-30235	33	7	(	(	PUNCT
ajst-30235	33	8	(	(	PUNCT
ajst-30235	33	9	,	,	PUNCT
ajst-30235	33	10	)	)	PUNCT
ajst-30235	33	11	)	)	PUNCT
ajst-30235	34	1	(	(	PUNCT
ajst-30235	34	2	(	(	PUNCT
ajst-30235	34	3	)	)	PUNCT
ajst-30235	34	4	)	)	PUNCT
ajst-30235	34	5	s	s	VERB
ajst-30235	34	6	f	f	PROPN
ajst-30235	34	7	z	z	PROPN
ajst-30235	34	8	w	w	PROPN
ajst-30235	34	9	s	s	PROPN
ajst-30235	34	10	g	g	PROPN
ajst-30235	34	11	z	z	PROPN
ajst-30235	34	12	w	w	PROPN
ajst-30235	34	13	s	s	PROPN
ajst-30235	34	14	w	w	PROPN
ajst-30235	34	15	w	w	PROPN
ajst-30235	34	16	z	z	PROPN
ajst-30235	34	17			X
ajst-30235	34	18			PROPN
ajst-30235	35	1			NUM
ajst-30235	35	2			NUM
ajst-30235	35	3			NUM
ajst-30235	35	4			NOUN
ajst-30235	35	5	(	(	PUNCT
ajst-30235	35	6	2	2	NUM
ajst-30235	35	7	)	)	PUNCT
ajst-30235	35	8	among	among	ADP
ajst-30235	35	9	them	they	PRON
ajst-30235	35	10	.	.	PUNCT
ajst-30235	36	1	w	w	PROPN
ajst-30235	36	2	∈	∈	PROPN
ajst-30235	36	3	r	r	NOUN
ajst-30235	36	4	,	,	PUNCT
ajst-30235	36	5	w	w	PROPN
ajst-30235	36	6	∈	∈	PROPN
ajst-30235	36	7	r	r	NOUN
ajst-30235	36	8	,	,	PUNCT
ajst-30235	36	9	δ	δ	PROPN
ajst-30235	36	10	is	be	AUX
ajst-30235	36	11	the	the	DET
ajst-30235	36	12	relu	relu	NOUN
ajst-30235	36	13	activation	activation	NOUN
ajst-30235	36	14	function	function	NOUN
ajst-30235	36	15	for	for	ADP
ajst-30235	36	16	the	the	DET
ajst-30235	36	17	fc	fc	PROPN
ajst-30235	36	18	layer	layer	NOUN
ajst-30235	36	19	,	,	PUNCT
ajst-30235	36	20	σ	σ	PROPN
ajst-30235	36	21	is	be	AUX
ajst-30235	36	22	the	the	DET
ajst-30235	36	23	sigmoid	sigmoid	NOUN
ajst-30235	36	24	activation	activation	NOUN
ajst-30235	36	25	function	function	NOUN
ajst-30235	36	26	for	for	ADP
ajst-30235	36	27	the	the	DET
ajst-30235	36	28	fc	fc	PROPN
ajst-30235	36	29	layer	layer	NOUN
ajst-30235	36	30	,	,	PUNCT
ajst-30235	36	31	w	w	PROPN
ajst-30235	36	32	,	,	PUNCT
ajst-30235	36	33	w	w	PROPN
ajst-30235	36	34	are	be	AUX
ajst-30235	36	35	fc	fc	PROPN
ajst-30235	36	36	layer	layer	NOUN
ajst-30235	36	37	weights	weight	NOUN
ajst-30235	36	38	.	.	PUNCT
ajst-30235	37	1	the	the	DET
ajst-30235	37	2	scale	scale	NOUN
ajst-30235	37	3	realizes	realize	VERB
ajst-30235	37	4	the	the	DET
ajst-30235	37	5	adaptive	adaptive	ADJ
ajst-30235	37	6	adjustment	adjustment	NOUN
ajst-30235	37	7	of	of	ADP
ajst-30235	37	8	channel	channel	NOUN
ajst-30235	37	9	features	feature	NOUN
ajst-30235	37	10	by	by	ADP
ajst-30235	37	11	multiplying	multiply	VERB
ajst-30235	37	12	each	each	DET
ajst-30235	37	13	channel	channel	NOUN
ajst-30235	37	14	weight	weight	NOUN
ajst-30235	37	15	obtained	obtain	VERB
ajst-30235	37	16	from	from	ADP
ajst-30235	37	17	the	the	DET
ajst-30235	37	18	excitation	excitation	NOUN
ajst-30235	37	19	computation	computation	NOUN
ajst-30235	37	20	,	,	PUNCT
ajst-30235	37	21	point	point	NOUN
ajst-30235	37	22	by	by	ADP
ajst-30235	37	23	point	point	NOUN
ajst-30235	37	24	,	,	PUNCT
ajst-30235	37	25	with	with	ADP
ajst-30235	37	26	each	each	DET
ajst-30235	37	27	element	element	NOUN
ajst-30235	37	28	within	within	ADP
ajst-30235	37	29	the	the	DET
ajst-30235	37	30	corresponding	corresponding	ADJ
ajst-30235	37	31	channel	channel	NOUN
ajst-30235	37	32	.	.	PUNCT
ajst-30235	38	1	after	after	ADP
ajst-30235	38	2	this	this	DET
ajst-30235	38	3	process	process	NOUN
ajst-30235	38	4	,	,	PUNCT
ajst-30235	38	5	the	the	DET
ajst-30235	38	6	feature	feature	NOUN
ajst-30235	38	7	mapping	map	VERB
ajst-30235	38	8	u	u	NOUN
ajst-30235	38	9	is	be	AUX
ajst-30235	38	10	reweighted	reweighte	VERB
ajst-30235	38	11	based	base	VERB
ajst-30235	38	12	on	on	ADP
ajst-30235	38	13	the	the	DET
ajst-30235	38	14	channel	channel	NOUN
ajst-30235	38	15	weights	weight	VERB
ajst-30235	38	16	to	to	PART
ajst-30235	38	17	generate	generate	VERB
ajst-30235	38	18	the	the	DET
ajst-30235	38	19	final	final	ADJ
ajst-30235	38	20	output	output	NOUN
ajst-30235	38	21	of	of	ADP
ajst-30235	38	22	the	the	DET
ajst-30235	38	23	se	se	PROPN
ajst-30235	38	24	module[13	module[13	PROPN
ajst-30235	38	25	]	]	PUNCT
ajst-30235	38	26	.	.	PUNCT
ajst-30235	39	1	2.2	2.2	NUM
ajst-30235	39	2	.	.	PUNCT
ajst-30235	40	1	convolutional	convolutional	ADJ
ajst-30235	40	2	neural	neural	ADJ
ajst-30235	40	3	networks	network	NOUN
ajst-30235	40	4	convolutional	convolutional	ADJ
ajst-30235	40	5	neural	neural	ADJ
ajst-30235	40	6	networks	network	NOUN
ajst-30235	40	7	is	be	AUX
ajst-30235	40	8	a	a	DET
ajst-30235	40	9	deep	deep	ADJ
ajst-30235	40	10	learning	learning	NOUN
ajst-30235	40	11	model	model	NOUN
ajst-30235	40	12	designed	design	VERB
ajst-30235	40	13	to	to	PART
ajst-30235	40	14	deal	deal	VERB
ajst-30235	40	15	with	with	ADP
ajst-30235	40	16	the	the	DET
ajst-30235	40	17	local	local	ADJ
ajst-30235	40	18	correlation	correlation	NOUN
ajst-30235	40	19	of	of	ADP
ajst-30235	40	20	data	datum	NOUN
ajst-30235	40	21	,	,	PUNCT
ajst-30235	40	22	compared	compare	VERB
ajst-30235	40	23	with	with	ADP
ajst-30235	40	24	the	the	DET
ajst-30235	40	25	traditional	traditional	ADJ
ajst-30235	40	26	fully	fully	ADV
ajst-30235	40	27	connected	connected	ADJ
ajst-30235	40	28	neural	neural	ADJ
ajst-30235	40	29	network	network	NOUN
ajst-30235	40	30	(	(	PUNCT
ajst-30235	40	31	cnn	cnn	PROPN
ajst-30235	40	32	)	)	PUNCT
ajst-30235	40	33	,	,	PUNCT
ajst-30235	40	34	cnn	cnn	PROPN
ajst-30235	40	35	effectively	effectively	ADV
ajst-30235	40	36	reduces	reduce	VERB
ajst-30235	40	37	the	the	DET
ajst-30235	40	38	model	model	NOUN
ajst-30235	40	39	complexity	complexity	NOUN
ajst-30235	40	40	and	and	CCONJ
ajst-30235	40	41	improves	improve	VERB
ajst-30235	40	42	the	the	DET
ajst-30235	40	43	feature	feature	NOUN
ajst-30235	40	44	extraction	extraction	NOUN
ajst-30235	40	45	capability	capability	NOUN
ajst-30235	40	46	through	through	ADP
ajst-30235	40	47	mechanisms	mechanism	NOUN
ajst-30235	40	48	such	such	ADJ
ajst-30235	40	49	as	as	ADP
ajst-30235	40	50	local	local	ADJ
ajst-30235	40	51	sensory	sensory	ADJ
ajst-30235	40	52	wildness	wildness	NOUN
ajst-30235	40	53	,	,	PUNCT
ajst-30235	40	54	weight	weight	NOUN
ajst-30235	40	55	sharing	sharing	NOUN
ajst-30235	40	56	and	and	CCONJ
ajst-30235	40	57	pooling[14	pooling[14	NOUN
ajst-30235	40	58	-	-	SYM
ajst-30235	40	59	16	16	NUM
ajst-30235	40	60	]	]	PUNCT
ajst-30235	40	61	.	.	PUNCT
ajst-30235	41	1	the	the	DET
ajst-30235	41	2	structure	structure	NOUN
ajst-30235	41	3	mainly	mainly	ADV
ajst-30235	41	4	consists	consist	VERB
ajst-30235	41	5	of	of	ADP
ajst-30235	41	6	convolutional	convolutional	ADJ
ajst-30235	41	7	layer	layer	NOUN
ajst-30235	41	8	,	,	PUNCT
ajst-30235	41	9	activation	activation	NOUN
ajst-30235	41	10	function	function	NOUN
ajst-30235	41	11	,	,	PUNCT
ajst-30235	41	12	pooling	pool	VERB
ajst-30235	41	13	layer	layer	NOUN
ajst-30235	41	14	,	,	PUNCT
ajst-30235	41	15	fully	fully	ADV
ajst-30235	41	16	connected	connected	ADJ
ajst-30235	41	17	layer	layer	NOUN
ajst-30235	41	18	and	and	CCONJ
ajst-30235	41	19	output	output	NOUN
ajst-30235	41	20	layer	layer	NOUN
ajst-30235	41	21	,	,	PUNCT
ajst-30235	41	22	where	where	SCONJ
ajst-30235	41	23	the	the	DET
ajst-30235	41	24	convolutional	convolutional	ADJ
ajst-30235	41	25	computation	computation	NOUN
ajst-30235	41	26	is	be	AUX
ajst-30235	41	27	represented	represent	VERB
ajst-30235	41	28	by	by	ADP
ajst-30235	41	29	equation	equation	NOUN
ajst-30235	41	30	(	(	PUNCT
ajst-30235	41	31	3	3	NUM
ajst-30235	41	32	)	)	PUNCT
ajst-30235	41	33	,	,	PUNCT
ajst-30235	41	34	and	and	CCONJ
ajst-30235	41	35	the	the	DET
ajst-30235	41	36	maximum	maximum	ADJ
ajst-30235	41	37	pooling	pooling	NOUN
ajst-30235	41	38	to	to	PART
ajst-30235	41	39	extract	extract	VERB
ajst-30235	41	40	the	the	DET
ajst-30235	41	41	key	key	ADJ
ajst-30235	41	42	features	feature	NOUN
ajst-30235	41	43	is	be	AUX
ajst-30235	41	44	computed	compute	VERB
ajst-30235	41	45	by	by	ADP
ajst-30235	41	46	equation	equation	NOUN
ajst-30235	41	47	(	(	PUNCT
ajst-30235	41	48	4	4	NUM
ajst-30235	41	49	)	)	PUNCT
ajst-30235	41	50	.	.	PUNCT
ajst-30235	42	1	,	,	PUNCT
ajst-30235	42	2	,	,	PUNCT
ajst-30235	42	3	,	,	PUNCT
ajst-30235	42	4	k	k	PROPN
ajst-30235	43	1	k	k	PROPN
ajst-30235	43	2	k	k	PROPN
ajst-30235	44	1	i	i	PRON
ajst-30235	44	2	j	j	VERB
ajst-30235	45	1	i	i	PRON
ajst-30235	45	2	m	m	VERB
ajst-30235	45	3	j	j	PROPN
ajst-30235	45	4	n	n	CCONJ
ajst-30235	45	5	m	m	VERB
ajst-30235	45	6	n	n	NOUN
ajst-30235	45	7	m	m	PROPN
ajst-30235	45	8	n	n	ADV
ajst-30235	45	9	y	y	PROPN
ajst-30235	45	10	x	x	PROPN
ajst-30235	46	1	w	w	ADP
ajst-30235	46	2	b	b	NOUN
ajst-30235	46	3			ADJ
ajst-30235	46	4			PROPN
ajst-30235	46	5			NOUN
ajst-30235	46	6	(	(	PUNCT
ajst-30235	46	7	3	3	NUM
ajst-30235	46	8	)	)	PUNCT
ajst-30235	46	9	,	,	PUNCT
ajst-30235	46	10	,	,	PUNCT
ajst-30235	46	11	max	max	PROPN
ajst-30235	46	12	(	(	PUNCT
ajst-30235	46	13	)	)	PUNCT
ajst-30235	46	14	,	,	PUNCT
ajst-30235	46	15	,	,	PUNCT
ajst-30235	46	16	i	i	PRON
ajst-30235	46	17	j	j	VERB
ajst-30235	47	1	i	i	PRON
ajst-30235	47	2	m	m	VERB
ajst-30235	47	3	j	j	PROPN
ajst-30235	47	4	ny	ny	PROPN
ajst-30235	47	5	x	x	PROPN
ajst-30235	47	6	m	m	VERB
ajst-30235	47	7	n	n	NUM
ajst-30235	47	8	p	p	NOUN
ajst-30235	47	9			ADJ
ajst-30235	47	10			NOUN
ajst-30235	47	11	(	(	PUNCT
ajst-30235	47	12	4	4	NUM
ajst-30235	47	13	)	)	PUNCT
ajst-30235	47	14	where	where	SCONJ
ajst-30235	47	15	x	x	PRON
ajst-30235	47	16	is	be	AUX
ajst-30235	47	17	the	the	DET
ajst-30235	47	18	input	input	NOUN
ajst-30235	47	19	feature	feature	NOUN
ajst-30235	47	20	,	,	PUNCT
ajst-30235	47	21	w	w	NOUN
ajst-30235	47	22	is	be	AUX
ajst-30235	47	23	the	the	DET
ajst-30235	47	24	convolution	convolution	NOUN
ajst-30235	47	25	kernel	kernel	PROPN
ajst-30235	47	26	weight	weight	PROPN
ajst-30235	47	27	,	,	PUNCT
ajst-30235	47	28	b	b	PROPN
ajst-30235	47	29	is	be	AUX
ajst-30235	47	30	the	the	DET
ajst-30235	47	31	bias	bias	NOUN
ajst-30235	47	32	term	term	NOUN
ajst-30235	47	33	,	,	PUNCT
ajst-30235	47	34	y	y	PROPN
ajst-30235	47	35	is	be	AUX
ajst-30235	47	36	the	the	DET
ajst-30235	47	37	convolution	convolution	NOUN
ajst-30235	47	38	output	output	NOUN
ajst-30235	47	39	,	,	PUNCT
ajst-30235	47	40	and	and	CCONJ
ajst-30235	47	41	p	p	NOUN
ajst-30235	47	42	is	be	AUX
ajst-30235	47	43	the	the	DET
ajst-30235	47	44	pooling	pooling	NOUN
ajst-30235	47	45	layer	layer	NOUN
ajst-30235	47	46	window	window	NOUN
ajst-30235	47	47	size	size	NOUN
ajst-30235	47	48	.	.	PUNCT
ajst-30235	48	1	2.3	2.3	NUM
ajst-30235	48	2	.	.	PUNCT
ajst-30235	48	3	bearing	bear	VERB
ajst-30235	48	4	fault	fault	NOUN
ajst-30235	48	5	diagnosis	diagnosis	NOUN
ajst-30235	48	6	method	method	NOUN
ajst-30235	48	7	based	base	VERB
ajst-30235	48	8	on	on	ADP
ajst-30235	48	9	secnn	secnn	PROPN
ajst-30235	48	10	in	in	ADP
ajst-30235	48	11	bearing	bear	VERB
ajst-30235	48	12	fault	fault	NOUN
ajst-30235	48	13	diagnosis	diagnosis	NOUN
ajst-30235	48	14	,	,	PUNCT
ajst-30235	48	15	vibration	vibration	NOUN
ajst-30235	48	16	signals	signal	NOUN
ajst-30235	48	17	usually	usually	ADV
ajst-30235	48	18	have	have	VERB
ajst-30235	48	19	complex	complex	ADJ
ajst-30235	48	20	spatio	spatio	ADJ
ajst-30235	48	21	-	-	PUNCT
ajst-30235	48	22	temporal	temporal	ADJ
ajst-30235	48	23	characteristics	characteristic	NOUN
ajst-30235	48	24	,	,	PUNCT
ajst-30235	48	25	and	and	CCONJ
ajst-30235	48	26	the	the	DET
ajst-30235	48	27	energy	energy	NOUN
ajst-30235	48	28	distribution	distribution	NOUN
ajst-30235	48	29	in	in	ADP
ajst-30235	48	30	different	different	ADJ
ajst-30235	48	31	frequency	frequency	NOUN
ajst-30235	48	32	bands	band	NOUN
ajst-30235	48	33	is	be	AUX
ajst-30235	48	34	closely	closely	ADV
ajst-30235	48	35	related	relate	VERB
ajst-30235	48	36	to	to	ADP
ajst-30235	48	37	the	the	DET
ajst-30235	48	38	fault	fault	NOUN
ajst-30235	48	39	type	type	NOUN
ajst-30235	48	40	.	.	PUNCT
ajst-30235	49	1	however	however	ADV
ajst-30235	49	2	,	,	PUNCT
ajst-30235	49	3	the	the	DET
ajst-30235	49	4	traditional	traditional	ADJ
ajst-30235	49	5	convolutional	convolutional	ADJ
ajst-30235	49	6	neural	neural	ADJ
ajst-30235	49	7	network	network	NOUN
ajst-30235	49	8	often	often	ADV
ajst-30235	49	9	assigns	assign	VERB
ajst-30235	49	10	the	the	DET
ajst-30235	49	11	same	same	ADJ
ajst-30235	49	12	weight	weight	NOUN
ajst-30235	49	13	to	to	ADP
ajst-30235	49	14	the	the	DET
ajst-30235	49	15	features	feature	NOUN
ajst-30235	49	16	of	of	ADP
ajst-30235	49	17	all	all	DET
ajst-30235	49	18	channels	channel	NOUN
ajst-30235	49	19	when	when	SCONJ
ajst-30235	49	20	processing	processing	NOUN
ajst-30235	49	21	vibration	vibration	NOUN
ajst-30235	49	22	signals	signal	NOUN
ajst-30235	49	23	,	,	PUNCT
ajst-30235	49	24	failing	fail	VERB
ajst-30235	49	25	to	to	PART
ajst-30235	49	26	fully	fully	ADV
ajst-30235	49	27	consider	consider	VERB
ajst-30235	49	28	the	the	DET
ajst-30235	49	29	importance	importance	NOUN
ajst-30235	49	30	of	of	ADP
ajst-30235	49	31	the	the	DET
ajst-30235	49	32	information	information	NOUN
ajst-30235	49	33	of	of	ADP
ajst-30235	49	34	different	different	ADJ
ajst-30235	49	35	channels	channel	NOUN
ajst-30235	49	36	,	,	PUNCT
ajst-30235	49	37	which	which	PRON
ajst-30235	49	38	may	may	AUX
ajst-30235	49	39	lead	lead	VERB
ajst-30235	49	40	to	to	ADP
ajst-30235	49	41	the	the	DET
ajst-30235	49	42	weakening	weakening	NOUN
ajst-30235	49	43	or	or	CCONJ
ajst-30235	49	44	loss	loss	NOUN
ajst-30235	49	45	of	of	ADP
ajst-30235	49	46	some	some	PRON
ajst-30235	49	47	of	of	ADP
ajst-30235	49	48	the	the	DET
ajst-30235	49	49	key	key	ADJ
ajst-30235	49	50	fault	fault	NOUN
ajst-30235	49	51	features	feature	VERB
ajst-30235	49	52	.	.	PUNCT
ajst-30235	50	1	the	the	DET
ajst-30235	50	2	convolutional	convolutional	ADJ
ajst-30235	50	3	neural	neural	ADJ
ajst-30235	50	4	network	network	NOUN
ajst-30235	50	5	combined	combine	VERB
ajst-30235	50	6	with	with	ADP
ajst-30235	50	7	the	the	DET
ajst-30235	50	8	channel	channel	NOUN
ajst-30235	50	9	attention	attention	NOUN
ajst-30235	50	10	network	network	NOUN
ajst-30235	50	11	shown	show	VERB
ajst-30235	50	12	in	in	ADP
ajst-30235	50	13	figure	figure	NOUN
ajst-30235	50	14	1	1	NUM
ajst-30235	50	15	can	can	AUX
ajst-30235	50	16	effectively	effectively	ADV
ajst-30235	50	17	enhance	enhance	VERB
ajst-30235	50	18	the	the	DET
ajst-30235	50	19	feature	feature	NOUN
ajst-30235	50	20	extraction	extraction	NOUN
ajst-30235	50	21	ability	ability	NOUN
ajst-30235	50	22	of	of	ADP
ajst-30235	50	23	the	the	DET
ajst-30235	50	24	model	model	NOUN
ajst-30235	50	25	and	and	CCONJ
ajst-30235	50	26	improve	improve	VERB
ajst-30235	50	27	the	the	DET
ajst-30235	50	28	accuracy	accuracy	NOUN
ajst-30235	50	29	of	of	ADP
ajst-30235	50	30	bearing	bear	VERB
ajst-30235	50	31	fault	fault	NOUN
ajst-30235	50	32	classification[17	classification[17	VERB
ajst-30235	50	33	]	]	PUNCT
ajst-30235	50	34	.	.	PUNCT
ajst-30235	51	1	figure	figure	NOUN
ajst-30235	51	2	1	1	NUM
ajst-30235	51	3	.	.	X
ajst-30235	52	1	se	se	PROPN
ajst-30235	52	2	-	-	PROPN
ajst-30235	52	3	cnn	cnn	PROPN
ajst-30235	52	4	structure	structure	NOUN
ajst-30235	52	5	the	the	DET
ajst-30235	52	6	whole	whole	ADJ
ajst-30235	52	7	algorithm	algorithm	NOUN
ajst-30235	52	8	model	model	NOUN
ajst-30235	52	9	is	be	AUX
ajst-30235	52	10	architected	architecte	VERB
ajst-30235	52	11	and	and	CCONJ
ajst-30235	52	12	trained	train	VERB
ajst-30235	52	13	on	on	ADP
ajst-30235	52	14	python3.8.3	python3.8.3	ADJ
ajst-30235	52	15	platform	platform	NOUN
ajst-30235	52	16	based	base	VERB
ajst-30235	52	17	on	on	ADP
ajst-30235	52	18	tensorflow	tensorflow	NOUN
ajst-30235	52	19	deep	deep	ADJ
ajst-30235	52	20	learning	learning	NOUN
ajst-30235	52	21	framework	framework	NOUN
ajst-30235	52	22	,	,	PUNCT
ajst-30235	52	23	and	and	CCONJ
ajst-30235	52	24	the	the	DET
ajst-30235	52	25	training	training	NOUN
ajst-30235	52	26	parameters	parameter	NOUN
ajst-30235	52	27	of	of	ADP
ajst-30235	52	28	se	se	PROPN
ajst-30235	52	29	-	-	NOUN
ajst-30235	52	30	cnn	cnn	PROPN
ajst-30235	52	31	bearing	bear	VERB
ajst-30235	52	32	fault	fault	NOUN
ajst-30235	52	33	diagnosis	diagnosis	NOUN
ajst-30235	52	34	method	method	NOUN
ajst-30235	52	35	are	be	AUX
ajst-30235	52	36	shown	show	VERB
ajst-30235	52	37	in	in	ADP
ajst-30235	52	38	table	table	NOUN
ajst-30235	52	39	1	1	NUM
ajst-30235	52	40	.	.	PUNCT
ajst-30235	52	41	table	table	NOUN
ajst-30235	52	42	1	1	NUM
ajst-30235	52	43	.	.	X
ajst-30235	53	1	se	se	PROPN
ajst-30235	53	2	-	-	PROPN
ajst-30235	53	3	cnn	cnn	PROPN
ajst-30235	53	4	training	training	NOUN
ajst-30235	53	5	parameter	parameter	NOUN
ajst-30235	53	6	learning	learn	VERB
ajst-30235	53	7	rate	rate	NOUN
ajst-30235	53	8	epochs	epoch	NOUN
ajst-30235	53	9	size	size	NOUN
ajst-30235	53	10	se	se	PROPN
ajst-30235	53	11	-	-	PROPN
ajst-30235	53	12	fc1	fc1	PROPN
ajst-30235	53	13	cnn	cnn	PROPN
ajst-30235	53	14	activation	activation	NOUN
ajst-30235	53	15	function	function	VERB
ajst-30235	53	16	0.001	0.001	NUM
ajst-30235	53	17	50	50	NUM
ajst-30235	53	18	512	512	NUM
ajst-30235	53	19	1/16	1/16	NUM
ajst-30235	53	20	relu	relu	NOUN
ajst-30235	53	21	3	3	NUM
ajst-30235	53	22	.	.	PUNCT
ajst-30235	54	1	experimental	experimental	ADJ
ajst-30235	54	2	examples	example	NOUN
ajst-30235	54	3	3.1	3.1	NUM
ajst-30235	54	4	.	.	PUNCT
ajst-30235	55	1	experimental	experimental	ADJ
ajst-30235	55	2	data	datum	NOUN
ajst-30235	55	3	the	the	DET
ajst-30235	55	4	experimental	experimental	ADJ
ajst-30235	55	5	data	datum	NOUN
ajst-30235	55	6	are	be	AUX
ajst-30235	55	7	provided	provide	VERB
ajst-30235	55	8	by	by	ADP
ajst-30235	55	9	the	the	DET
ajst-30235	55	10	bearing	bear	VERB
ajst-30235	55	11	experiment	experiment	NOUN
ajst-30235	55	12	center	center	NOUN
ajst-30235	55	13	of	of	ADP
ajst-30235	55	14	case	case	NOUN
ajst-30235	55	15	western	western	PROPN
ajst-30235	55	16	reserve	reserve	PROPN
ajst-30235	55	17	university	university	PROPN
ajst-30235	55	18	(	(	PUNCT
ajst-30235	55	19	cwru	cwru	PROPN
ajst-30235	55	20	)	)	PUNCT
ajst-30235	55	21	,	,	PUNCT
ajst-30235	55	22	and	and	CCONJ
ajst-30235	55	23	the	the	DET
ajst-30235	55	24	main	main	ADJ
ajst-30235	55	25	components	component	NOUN
ajst-30235	55	26	of	of	ADP
ajst-30235	55	27	the	the	DET
ajst-30235	55	28	test	test	NOUN
ajst-30235	55	29	bench	bench	NOUN
ajst-30235	55	30	include	include	VERB
ajst-30235	55	31	traction	traction	NOUN
ajst-30235	55	32	motor	motor	NOUN
ajst-30235	55	33	,	,	PUNCT
ajst-30235	55	34	torque	torque	NOUN
ajst-30235	55	35	sensor	sensor	NOUN
ajst-30235	55	36	and	and	CCONJ
ajst-30235	55	37	dynamometer	dynamometer	NOUN
ajst-30235	55	38	,	,	PUNCT
ajst-30235	55	39	and	and	CCONJ
ajst-30235	55	40	the	the	DET
ajst-30235	55	41	motor	motor	NOUN
ajst-30235	55	42	shaft	shaft	NOUN
ajst-30235	55	43	support	support	NOUN
ajst-30235	55	44	bearing	bear	VERB
ajst-30235	55	45	model	model	NOUN
ajst-30235	55	46	is	be	AUX
ajst-30235	55	47	6205	6205	NUM
ajst-30235	55	48	-	-	PUNCT
ajst-30235	55	49	2rs	2rs	ADJ
ajst-30235	55	50	jem	jem	PROPN
ajst-30235	55	51	skf	skf	PROPN
ajst-30235	55	52	.	.	PUNCT
ajst-30235	56	1	the	the	DET
ajst-30235	56	2	experimental	experimental	ADJ
ajst-30235	56	3	data	datum	NOUN
ajst-30235	56	4	in	in	ADP
ajst-30235	56	5	this	this	DET
ajst-30235	56	6	paper	paper	NOUN
ajst-30235	56	7	are	be	AUX
ajst-30235	56	8	collected	collect	VERB
ajst-30235	56	9	from	from	ADP
ajst-30235	56	10	the	the	DET
ajst-30235	56	11	motor	motor	NOUN
ajst-30235	56	12	drive	drive	NOUN
ajst-30235	56	13	end	end	NOUN
ajst-30235	56	14	bearings	bearing	NOUN
ajst-30235	56	15	in	in	ADP
ajst-30235	56	16	different	different	ADJ
ajst-30235	56	17	health	health	NOUN
ajst-30235	56	18	states	state	NOUN
ajst-30235	56	19	,	,	PUNCT
ajst-30235	56	20	the	the	DET
ajst-30235	56	21	sampling	sample	VERB
ajst-30235	56	22	frequency	frequency	NOUN
ajst-30235	56	23	are	be	AUX
ajst-30235	56	24	12khz	12khz	NOUN
ajst-30235	56	25	,	,	PUNCT
ajst-30235	56	26	according	accord	VERB
ajst-30235	56	27	to	to	ADP
ajst-30235	56	28	the	the	DET
ajst-30235	56	29	different	different	ADJ
ajst-30235	56	30	conditions	condition	NOUN
ajst-30235	56	31	of	of	ADP
ajst-30235	56	32	the	the	DET
ajst-30235	56	33	construction	construction	NOUN
ajst-30235	56	34	of	of	ADP
ajst-30235	56	35	the	the	DET
ajst-30235	56	36	data	datum	NOUN
ajst-30235	56	37	set	set	VERB
ajst-30235	56	38	,	,	PUNCT
ajst-30235	56	39	the	the	DET
ajst-30235	56	40	data	datum	NOUN
ajst-30235	56	41	set	set	VERB
ajst-30235	56	42	training	training	NOUN
ajst-30235	56	43	samples	sample	NOUN
ajst-30235	56	44	and	and	CCONJ
ajst-30235	56	45	test	test	NOUN
ajst-30235	56	46	samples	sample	NOUN
ajst-30235	56	47	in	in	ADP
ajst-30235	56	48	the	the	DET
ajst-30235	56	49	ratio	ratio	NOUN
ajst-30235	56	50	of	of	ADP
ajst-30235	56	51	0.8:0.2	0.8:0.2	NUM
ajst-30235	56	52	,	,	PUNCT
ajst-30235	56	53	and	and	CCONJ
ajst-30235	56	54	the	the	DET
ajst-30235	56	55	use	use	NOUN
ajst-30235	56	56	of	of	ADP
ajst-30235	56	57	the	the	DET
ajst-30235	56	58	data	datum	NOUN
ajst-30235	56	59	amplification	amplification	NOUN
ajst-30235	56	60	technology	technology	NOUN
ajst-30235	56	61	,	,	PUNCT
ajst-30235	56	62	the	the	DET
ajst-30235	56	63	length	length	NOUN
ajst-30235	56	64	of	of	ADP
ajst-30235	56	65	each	each	DET
ajst-30235	56	66	sample	sample	NOUN
ajst-30235	56	67	is	be	AUX
ajst-30235	56	68	2048	2048	NUM
ajst-30235	56	69	,	,	PUNCT
ajst-30235	56	70	and	and	CCONJ
ajst-30235	56	71	normalized	normalize	VERB
ajst-30235	56	72	,	,	PUNCT
ajst-30235	56	73	as	as	SCONJ
ajst-30235	56	74	shown	show	VERB
ajst-30235	56	75	in	in	ADP
ajst-30235	56	76	table	table	NOUN
ajst-30235	56	77	2	2	NUM
ajst-30235	56	78	.	.	NOUN
ajst-30235	56	79	373	373	NUM
ajst-30235	56	80	table	table	NOUN
ajst-30235	56	81	2	2	NUM
ajst-30235	56	82	.	.	PUNCT
ajst-30235	56	83	specific	specific	ADJ
ajst-30235	56	84	components	component	NOUN
ajst-30235	56	85	of	of	ADP
ajst-30235	56	86	the	the	DET
ajst-30235	56	87	data	datum	NOUN
ajst-30235	56	88	set	set	VERB
ajst-30235	56	89	fault	fault	NOUN
ajst-30235	56	90	location	location	NOUN
ajst-30235	56	91	pitting	pit	VERB
ajst-30235	56	92	diameter(mil	diameter(mil	NOUN
ajst-30235	56	93	)	)	PUNCT
ajst-30235	56	94	category	category	NOUN
ajst-30235	56	95	tag	tag	NOUN
ajst-30235	56	96	number	number	NOUN
ajst-30235	56	97	of	of	ADP
ajst-30235	56	98	training	training	NOUN
ajst-30235	56	99	/	/	SYM
ajst-30235	56	100	testing	testing	NOUN
ajst-30235	56	101	samples	sample	NOUN
ajst-30235	56	102	0.001	0.001	NUM
ajst-30235	56	103	50	50	NUM
ajst-30235	56	104	512	512	NUM
ajst-30235	56	105	1/16	1/16	NUM
ajst-30235	56	106	normal	normal	ADJ
ajst-30235	56	107	normal	normal	ADJ
ajst-30235	56	108	400/100	400/100	PROPN
ajst-30235	56	109	inner	inner	ADJ
ajst-30235	56	110	race	race	NOUN
ajst-30235	56	111	7	7	NUM
ajst-30235	56	112	ir_07	ir_07	PROPN
ajst-30235	56	113	400/100	400/100	PROPN
ajst-30235	56	114	14	14	NUM
ajst-30235	56	115	ir_14	ir_14	NOUN
ajst-30235	56	116	400/100	400/100	PROPN
ajst-30235	56	117	21	21	NUM
ajst-30235	56	118	ir_21	ir_21	PROPN
ajst-30235	56	119	400/100	400/100	PROPN
ajst-30235	56	120	outer	outer	ADJ
ajst-30235	56	121	race	race	NOUN
ajst-30235	56	122	7	7	NUM
ajst-30235	56	123	or_07	or_07	PROPN
ajst-30235	56	124	400/100	400/100	PROPN
ajst-30235	56	125	14	14	NUM
ajst-30235	56	126	or_14	or_14	PROPN
ajst-30235	56	127	400/100	400/100	PROPN
ajst-30235	56	128	21	21	NUM
ajst-30235	56	129	or_21	or_21	PROPN
ajst-30235	56	130	400/100	400/100	PROPN
ajst-30235	56	131	ball	ball	NOUN
ajst-30235	56	132	7	7	NUM
ajst-30235	56	133	ball_07	ball_07	NOUN
ajst-30235	56	134	400/100	400/100	PROPN
ajst-30235	56	135	14	14	NUM
ajst-30235	56	136	ball_14	ball_14	NOUN
ajst-30235	56	137	400/100	400/100	PROPN
ajst-30235	56	138	21	21	NUM
ajst-30235	56	139	ball_21	ball_21	X
ajst-30235	57	1	400/100	400/100	NUM
ajst-30235	57	2	3.2	3.2	NUM
ajst-30235	57	3	.	.	PUNCT
ajst-30235	57	4	evaluation	evaluation	NOUN
ajst-30235	57	5	indicator	indicator	NOUN
ajst-30235	57	6	in	in	ADP
ajst-30235	57	7	order	order	NOUN
ajst-30235	57	8	to	to	PART
ajst-30235	57	9	comprehensively	comprehensively	ADV
ajst-30235	57	10	evaluate	evaluate	VERB
ajst-30235	57	11	the	the	DET
ajst-30235	57	12	performance	performance	NOUN
ajst-30235	57	13	of	of	ADP
ajst-30235	57	14	the	the	DET
ajst-30235	57	15	improved	improved	ADJ
ajst-30235	57	16	se	se	PROPN
ajst-30235	57	17	-	-	ADJ
ajst-30235	57	18	cnn	cnn	ADJ
ajst-30235	57	19	model	model	NOUN
ajst-30235	57	20	in	in	ADP
ajst-30235	57	21	the	the	DET
ajst-30235	57	22	bearing	bear	VERB
ajst-30235	57	23	fault	fault	NOUN
ajst-30235	57	24	diagnosis	diagnosis	NOUN
ajst-30235	57	25	task	task	NOUN
ajst-30235	57	26	,	,	PUNCT
ajst-30235	57	27	macro	macro	NOUN
ajst-30235	57	28	-	-	NOUN
ajst-30235	57	29	f1	f1	ADJ
ajst-30235	57	30	,	,	PUNCT
ajst-30235	57	31	recall	recall	NOUN
ajst-30235	57	32	,	,	PUNCT
ajst-30235	57	33	accuracy	accuracy	NOUN
ajst-30235	57	34	and	and	CCONJ
ajst-30235	57	35	precision	precision	NOUN
ajst-30235	57	36	are	be	AUX
ajst-30235	57	37	selected	select	VERB
ajst-30235	57	38	as	as	ADP
ajst-30235	57	39	the	the	DET
ajst-30235	57	40	main	main	ADJ
ajst-30235	57	41	evaluation	evaluation	NOUN
ajst-30235	57	42	indexes	index	NOUN
ajst-30235	57	43	in	in	ADP
ajst-30235	57	44	this	this	DET
ajst-30235	57	45	paper	paper	NOUN
ajst-30235	57	46	.	.	PUNCT
ajst-30235	58	1	these	these	DET
ajst-30235	58	2	indexes	index	NOUN
ajst-30235	58	3	can	can	AUX
ajst-30235	58	4	comprehensively	comprehensively	ADV
ajst-30235	58	5	reflect	reflect	VERB
ajst-30235	58	6	the	the	DET
ajst-30235	58	7	classification	classification	NOUN
ajst-30235	58	8	effect	effect	NOUN
ajst-30235	58	9	of	of	ADP
ajst-30235	58	10	the	the	DET
ajst-30235	58	11	model	model	NOUN
ajst-30235	58	12	in	in	ADP
ajst-30235	58	13	different	different	ADJ
ajst-30235	58	14	fault	fault	NOUN
ajst-30235	58	15	categories	category	NOUN
ajst-30235	58	16	and	and	CCONJ
ajst-30235	58	17	ensure	ensure	VERB
ajst-30235	58	18	its	its	PRON
ajst-30235	58	19	generalization	generalization	NOUN
ajst-30235	58	20	ability	ability	NOUN
ajst-30235	58	21	and	and	CCONJ
ajst-30235	58	22	stability	stability	NOUN
ajst-30235	58	23	.	.	PUNCT
ajst-30235	59	1	1.accuracy	1.accuracy	NUM
ajst-30235	59	2	:	:	PUNCT
ajst-30235	59	3	indicates	indicate	VERB
ajst-30235	59	4	the	the	DET
ajst-30235	59	5	correct	correct	ADJ
ajst-30235	59	6	rate	rate	NOUN
ajst-30235	59	7	of	of	ADP
ajst-30235	59	8	overall	overall	ADJ
ajst-30235	59	9	classification	classification	NOUN
ajst-30235	59	10	of	of	ADP
ajst-30235	59	11	the	the	DET
ajst-30235	59	12	model	model	NOUN
ajst-30235	59	13	,	,	PUNCT
ajst-30235	59	14	i.e.	i.e.	X
ajst-30235	59	15	the	the	DET
ajst-30235	59	16	proportion	proportion	NOUN
ajst-30235	59	17	of	of	ADP
ajst-30235	59	18	correctly	correctly	ADV
ajst-30235	59	19	classified	classify	VERB
ajst-30235	59	20	samples	sample	NOUN
ajst-30235	59	21	to	to	ADP
ajst-30235	59	22	all	all	DET
ajst-30235	59	23	samples	sample	NOUN
ajst-30235	59	24	.	.	PUNCT
ajst-30235	60	1	2.precision	2.precision	NUM
ajst-30235	60	2	:	:	PUNCT
ajst-30235	60	3	indicates	indicate	VERB
ajst-30235	60	4	the	the	DET
ajst-30235	60	5	degree	degree	NOUN
ajst-30235	60	6	of	of	ADP
ajst-30235	60	7	accuracy	accuracy	NOUN
ajst-30235	60	8	of	of	ADP
ajst-30235	60	9	the	the	DET
ajst-30235	60	10	model	model	NOUN
ajst-30235	60	11	's	's	PART
ajst-30235	60	12	prediction	prediction	NOUN
ajst-30235	60	13	of	of	ADP
ajst-30235	60	14	a	a	DET
ajst-30235	60	15	category	category	NOUN
ajst-30235	60	16	,	,	PUNCT
ajst-30235	60	17	reflecting	reflect	VERB
ajst-30235	60	18	how	how	SCONJ
ajst-30235	60	19	many	many	ADJ
ajst-30235	60	20	of	of	ADP
ajst-30235	60	21	the	the	DET
ajst-30235	60	22	samples	sample	NOUN
ajst-30235	60	23	predicted	predict	VERB
ajst-30235	60	24	to	to	PART
ajst-30235	60	25	be	be	AUX
ajst-30235	60	26	in	in	ADP
ajst-30235	60	27	that	that	DET
ajst-30235	60	28	category	category	NOUN
ajst-30235	60	29	actually	actually	ADV
ajst-30235	60	30	belong	belong	VERB
ajst-30235	60	31	to	to	ADP
ajst-30235	60	32	that	that	DET
ajst-30235	60	33	category	category	NOUN
ajst-30235	60	34	.	.	PUNCT
ajst-30235	61	1	3.recall	3.recall	NUM
ajst-30235	61	2	:	:	PUNCT
ajst-30235	61	3	measures	measure	VERB
ajst-30235	61	4	the	the	DET
ajst-30235	61	5	model	model	NOUN
ajst-30235	61	6	's	's	PART
ajst-30235	61	7	ability	ability	NOUN
ajst-30235	61	8	to	to	PART
ajst-30235	61	9	recognize	recognize	VERB
ajst-30235	61	10	a	a	DET
ajst-30235	61	11	category	category	NOUN
ajst-30235	61	12	.	.	PUNCT
ajst-30235	62	1	4.macro	4.macro	NUM
ajst-30235	62	2	-	-	NOUN
ajst-30235	62	3	f1	f1	NOUN
ajst-30235	62	4	:	:	PUNCT
ajst-30235	62	5	calculates	calculate	VERB
ajst-30235	62	6	the	the	DET
ajst-30235	62	7	arithmetic	arithmetic	ADJ
ajst-30235	62	8	mean	mean	NOUN
ajst-30235	62	9	of	of	ADP
ajst-30235	62	10	f1	f1	NOUN
ajst-30235	62	11	-	-	PUNCT
ajst-30235	62	12	score	score	NOUN
ajst-30235	62	13	for	for	ADP
ajst-30235	62	14	all	all	DET
ajst-30235	62	15	categories	category	NOUN
ajst-30235	62	16	,	,	PUNCT
ajst-30235	62	17	which	which	PRON
ajst-30235	62	18	is	be	AUX
ajst-30235	62	19	used	use	VERB
ajst-30235	62	20	to	to	PART
ajst-30235	62	21	evaluate	evaluate	VERB
ajst-30235	62	22	the	the	DET
ajst-30235	62	23	classification	classification	NOUN
ajst-30235	62	24	effect	effect	NOUN
ajst-30235	62	25	of	of	ADP
ajst-30235	62	26	different	different	ADJ
ajst-30235	62	27	categories	category	NOUN
ajst-30235	62	28	in	in	ADP
ajst-30235	62	29	a	a	DET
ajst-30235	62	30	balanced	balanced	ADJ
ajst-30235	62	31	way	way	NOUN
ajst-30235	62	32	.	.	PUNCT
ajst-30235	63	1	with	with	ADP
ajst-30235	63	2	these	these	DET
ajst-30235	63	3	indicators	indicator	NOUN
ajst-30235	63	4	,	,	PUNCT
ajst-30235	63	5	this	this	DET
ajst-30235	63	6	paper	paper	NOUN
ajst-30235	63	7	is	be	AUX
ajst-30235	63	8	able	able	ADJ
ajst-30235	63	9	to	to	PART
ajst-30235	63	10	comprehensively	comprehensively	ADV
ajst-30235	63	11	evaluate	evaluate	VERB
ajst-30235	63	12	the	the	DET
ajst-30235	63	13	performance	performance	NOUN
ajst-30235	63	14	of	of	ADP
ajst-30235	63	15	the	the	DET
ajst-30235	63	16	se	se	PROPN
ajst-30235	63	17	-	-	PROPN
ajst-30235	63	18	cnn	cnn	PROPN
ajst-30235	63	19	model	model	NOUN
ajst-30235	63	20	in	in	ADP
ajst-30235	63	21	the	the	DET
ajst-30235	63	22	bearing	bear	VERB
ajst-30235	63	23	fault	fault	NOUN
ajst-30235	63	24	diagnosis	diagnosis	NOUN
ajst-30235	63	25	task	task	NOUN
ajst-30235	63	26	and	and	CCONJ
ajst-30235	63	27	verify	verify	VERB
ajst-30235	63	28	its	its	PRON
ajst-30235	63	29	improvement	improvement	NOUN
ajst-30235	63	30	.	.	PUNCT
ajst-30235	64	1	3.3	3.3	NUM
ajst-30235	64	2	.	.	PUNCT
ajst-30235	65	1	experimental	experimental	ADJ
ajst-30235	65	2	results	result	NOUN
ajst-30235	65	3	and	and	CCONJ
ajst-30235	65	4	analysis	analysis	NOUN
ajst-30235	65	5	in	in	ADP
ajst-30235	65	6	this	this	DET
ajst-30235	65	7	experiment	experiment	NOUN
ajst-30235	65	8	,	,	PUNCT
ajst-30235	65	9	a	a	DET
ajst-30235	65	10	fault	fault	NOUN
ajst-30235	65	11	diagnosis	diagnosis	NOUN
ajst-30235	65	12	task	task	NOUN
ajst-30235	65	13	was	be	AUX
ajst-30235	65	14	performed	perform	VERB
ajst-30235	65	15	on	on	ADP
ajst-30235	65	16	the	the	DET
ajst-30235	65	17	cwru	cwru	NOUN
ajst-30235	65	18	bearing	bear	VERB
ajst-30235	65	19	dataset	dataset	NOUN
ajst-30235	65	20	based	base	VERB
ajst-30235	65	21	on	on	ADP
ajst-30235	65	22	the	the	DET
ajst-30235	65	23	se	se	PROPN
ajst-30235	65	24	-	-	PROPN
ajst-30235	65	25	cnn	cnn	PROPN
ajst-30235	65	26	model	model	NOUN
ajst-30235	65	27	.	.	PUNCT
ajst-30235	66	1	the	the	DET
ajst-30235	66	2	classification	classification	NOUN
ajst-30235	66	3	effect	effect	NOUN
ajst-30235	66	4	of	of	ADP
ajst-30235	66	5	the	the	DET
ajst-30235	66	6	model	model	NOUN
ajst-30235	66	7	is	be	AUX
ajst-30235	66	8	further	far	ADV
ajst-30235	66	9	analyzed	analyze	VERB
ajst-30235	66	10	by	by	ADP
ajst-30235	66	11	combining	combine	VERB
ajst-30235	66	12	the	the	DET
ajst-30235	66	13	loss	loss	NOUN
ajst-30235	66	14	value	value	NOUN
ajst-30235	66	15	iteration	iteration	NOUN
ajst-30235	66	16	curve	curve	NOUN
ajst-30235	66	17	and	and	CCONJ
ajst-30235	66	18	confusion	confusion	NOUN
ajst-30235	66	19	matrix	matrix	NOUN
ajst-30235	66	20	during	during	ADP
ajst-30235	66	21	the	the	DET
ajst-30235	66	22	model	model	NOUN
ajst-30235	66	23	training	training	NOUN
ajst-30235	66	24	process	process	NOUN
ajst-30235	66	25	.	.	PUNCT
ajst-30235	67	1	the	the	DET
ajst-30235	67	2	loss	loss	NOUN
ajst-30235	67	3	iteration	iteration	NOUN
ajst-30235	67	4	curve	curve	NOUN
ajst-30235	67	5	is	be	AUX
ajst-30235	67	6	shown	show	VERB
ajst-30235	67	7	in	in	ADP
ajst-30235	67	8	fig	fig	NOUN
ajst-30235	67	9	.	.	PUNCT
ajst-30235	68	1	2	2	NUM
ajst-30235	68	2	,	,	PUNCT
ajst-30235	68	3	where	where	SCONJ
ajst-30235	68	4	the	the	DET
ajst-30235	68	5	loss	loss	NOUN
ajst-30235	68	6	value	value	NOUN
ajst-30235	68	7	gradually	gradually	ADV
ajst-30235	68	8	decreases	decrease	VERB
ajst-30235	68	9	as	as	ADP
ajst-30235	68	10	training	training	NOUN
ajst-30235	68	11	proceeds	proceed	NOUN
ajst-30235	68	12	,	,	PUNCT
ajst-30235	68	13	indicating	indicate	VERB
ajst-30235	68	14	that	that	SCONJ
ajst-30235	68	15	the	the	DET
ajst-30235	68	16	model	model	NOUN
ajst-30235	68	17	is	be	AUX
ajst-30235	68	18	continuously	continuously	ADV
ajst-30235	68	19	learning	learn	VERB
ajst-30235	68	20	and	and	CCONJ
ajst-30235	68	21	optimizing	optimize	VERB
ajst-30235	68	22	its	its	PRON
ajst-30235	68	23	weights	weight	NOUN
ajst-30235	68	24	.	.	PUNCT
ajst-30235	69	1	the	the	DET
ajst-30235	69	2	smooth	smooth	ADJ
ajst-30235	69	3	decrease	decrease	NOUN
ajst-30235	69	4	in	in	ADP
ajst-30235	69	5	the	the	DET
ajst-30235	69	6	training	training	NOUN
ajst-30235	69	7	process	process	NOUN
ajst-30235	69	8	reflects	reflect	VERB
ajst-30235	69	9	the	the	DET
ajst-30235	69	10	good	good	ADJ
ajst-30235	69	11	convergence	convergence	NOUN
ajst-30235	69	12	of	of	ADP
ajst-30235	69	13	the	the	DET
ajst-30235	69	14	model	model	NOUN
ajst-30235	69	15	and	and	CCONJ
ajst-30235	69	16	indicates	indicate	VERB
ajst-30235	69	17	that	that	SCONJ
ajst-30235	69	18	the	the	DET
ajst-30235	69	19	training	training	NOUN
ajst-30235	69	20	data	data	NOUN
ajst-30235	69	21	is	be	AUX
ajst-30235	69	22	effectively	effectively	ADV
ajst-30235	69	23	fitted	fit	VERB
ajst-30235	69	24	.	.	PUNCT
ajst-30235	70	1	figure	figure	NOUN
ajst-30235	70	2	2	2	NUM
ajst-30235	70	3	.	.	PUNCT
ajst-30235	70	4	loss	loss	NOUN
ajst-30235	70	5	curve	curve	NOUN
ajst-30235	70	6	figure	figure	NOUN
ajst-30235	70	7	3	3	NUM
ajst-30235	70	8	shows	show	VERB
ajst-30235	70	9	the	the	DET
ajst-30235	70	10	confusion	confusion	NOUN
ajst-30235	70	11	matrix	matrix	NOUN
ajst-30235	70	12	of	of	ADP
ajst-30235	70	13	the	the	DET
ajst-30235	70	14	model	model	NOUN
ajst-30235	70	15	on	on	ADP
ajst-30235	70	16	the	the	DET
ajst-30235	70	17	test	test	NOUN
ajst-30235	70	18	set	set	VERB
ajst-30235	70	19	.	.	PUNCT
ajst-30235	71	1	as	as	SCONJ
ajst-30235	71	2	can	can	AUX
ajst-30235	71	3	be	be	AUX
ajst-30235	71	4	seen	see	VERB
ajst-30235	71	5	from	from	ADP
ajst-30235	71	6	the	the	DET
ajst-30235	71	7	confusion	confusion	NOUN
ajst-30235	71	8	matrix	matrix	NOUN
ajst-30235	71	9	,	,	PUNCT
ajst-30235	71	10	the	the	DET
ajst-30235	71	11	vast	vast	ADJ
ajst-30235	71	12	majority	majority	NOUN
ajst-30235	71	13	of	of	ADP
ajst-30235	71	14	the	the	DET
ajst-30235	71	15	test	test	NOUN
ajst-30235	71	16	samples	sample	NOUN
ajst-30235	71	17	are	be	AUX
ajst-30235	71	18	correctly	correctly	ADV
ajst-30235	71	19	categorized	categorize	VERB
ajst-30235	71	20	and	and	CCONJ
ajst-30235	71	21	have	have	VERB
ajst-30235	71	22	large	large	ADJ
ajst-30235	71	23	values	value	NOUN
ajst-30235	71	24	on	on	ADP
ajst-30235	71	25	the	the	DET
ajst-30235	71	26	diagonal	diagonal	ADJ
ajst-30235	71	27	line	line	NOUN
ajst-30235	71	28	,	,	PUNCT
ajst-30235	71	29	indicating	indicate	VERB
ajst-30235	71	30	that	that	SCONJ
ajst-30235	71	31	the	the	DET
ajst-30235	71	32	model	model	NOUN
ajst-30235	71	33	makes	make	VERB
ajst-30235	71	34	accurate	accurate	ADJ
ajst-30235	71	35	predictions	prediction	NOUN
ajst-30235	71	36	on	on	ADP
ajst-30235	71	37	most	most	ADJ
ajst-30235	71	38	of	of	ADP
ajst-30235	71	39	the	the	DET
ajst-30235	71	40	categories	category	NOUN
ajst-30235	71	41	.	.	PUNCT
ajst-30235	72	1	however	however	ADV
ajst-30235	72	2	,	,	PUNCT
ajst-30235	72	3	the	the	DET
ajst-30235	72	4	model	model	NOUN
ajst-30235	72	5	is	be	AUX
ajst-30235	72	6	prone	prone	ADJ
ajst-30235	72	7	to	to	ADP
ajst-30235	72	8	confusion	confusion	NOUN
ajst-30235	72	9	in	in	ADP
ajst-30235	72	10	the	the	DET
ajst-30235	72	11	failure	failure	NOUN
ajst-30235	72	12	type	type	NOUN
ajst-30235	72	13	of	of	ADP
ajst-30235	72	14	17	17	NUM
ajst-30235	72	15	mil	mil	NOUN
ajst-30235	72	16	for	for	ADP
ajst-30235	72	17	the	the	DET
ajst-30235	72	18	outer	outer	ADJ
ajst-30235	72	19	ring	ring	NOUN
ajst-30235	72	20	and	and	CCONJ
ajst-30235	72	21	7	7	NUM
ajst-30235	72	22	mil	mil	NOUN
ajst-30235	72	23	for	for	ADP
ajst-30235	72	24	the	the	DET
ajst-30235	72	25	rolling	rolling	ADJ
ajst-30235	72	26	body	body	NOUN
ajst-30235	72	27	.	.	PUNCT
ajst-30235	73	1	374	374	NUM
ajst-30235	73	2	figure	figure	NOUN
ajst-30235	73	3	3	3	NUM
ajst-30235	73	4	.	.	PUNCT
ajst-30235	73	5	confusion	confusion	NOUN
ajst-30235	73	6	matrix	matrix	NOUN
ajst-30235	73	7	in	in	ADP
ajst-30235	73	8	order	order	NOUN
ajst-30235	73	9	to	to	PART
ajst-30235	73	10	verify	verify	VERB
ajst-30235	73	11	the	the	DET
ajst-30235	73	12	effectiveness	effectiveness	NOUN
ajst-30235	73	13	of	of	ADP
ajst-30235	73	14	se	se	ADJ
ajst-30235	73	15	-	-	PROPN
ajst-30235	73	16	cnn	cnn	PROPN
ajst-30235	73	17	model	model	NOUN
ajst-30235	73	18	in	in	ADP
ajst-30235	73	19	this	this	DET
ajst-30235	73	20	experimental	experimental	ADJ
ajst-30235	73	21	task	task	NOUN
ajst-30235	73	22	,	,	PUNCT
ajst-30235	73	23	network	network	NOUN
ajst-30235	73	24	models	model	NOUN
ajst-30235	73	25	with	with	ADP
ajst-30235	73	26	the	the	DET
ajst-30235	73	27	same	same	ADJ
ajst-30235	73	28	depth	depth	NOUN
ajst-30235	73	29	and	and	CCONJ
ajst-30235	73	30	different	different	ADJ
ajst-30235	73	31	structures	structure	NOUN
ajst-30235	73	32	are	be	AUX
ajst-30235	73	33	built	build	VERB
ajst-30235	73	34	,	,	PUNCT
ajst-30235	73	35	which	which	PRON
ajst-30235	73	36	are	be	AUX
ajst-30235	73	37	resnet	resnet	ADJ
ajst-30235	73	38	model	model	NOUN
ajst-30235	73	39	,	,	PUNCT
ajst-30235	73	40	lstm	lstm	NOUN
ajst-30235	73	41	model	model	NOUN
ajst-30235	73	42	and	and	CCONJ
ajst-30235	73	43	original	original	ADJ
ajst-30235	73	44	cnn	cnn	PROPN
ajst-30235	73	45	model	model	NOUN
ajst-30235	73	46	,	,	PUNCT
ajst-30235	73	47	and	and	CCONJ
ajst-30235	73	48	the	the	DET
ajst-30235	73	49	comparison	comparison	NOUN
ajst-30235	73	50	results	result	NOUN
ajst-30235	73	51	are	be	AUX
ajst-30235	73	52	shown	show	VERB
ajst-30235	73	53	in	in	ADP
ajst-30235	73	54	table	table	NOUN
ajst-30235	73	55	3	3	NUM
ajst-30235	73	56	.	.	PUNCT
ajst-30235	73	57	table	table	NOUN
ajst-30235	73	58	3	3	NUM
ajst-30235	73	59	.	.	PUNCT
ajst-30235	74	1	comparison	comparison	NOUN
ajst-30235	74	2	of	of	ADP
ajst-30235	74	3	training	training	NOUN
ajst-30235	74	4	results	result	NOUN
ajst-30235	74	5	of	of	ADP
ajst-30235	74	6	each	each	DET
ajst-30235	74	7	model	model	NOUN
ajst-30235	74	8	on	on	ADP
ajst-30235	74	9	the	the	DET
ajst-30235	74	10	dataset	dataset	ADJ
ajst-30235	74	11	average	average	ADJ
ajst-30235	74	12	precision	precision	NOUN
ajst-30235	74	13	recall	recall	NOUN
ajst-30235	74	14	f1	f1	NOUN
ajst-30235	74	15	-	-	PUNCT
ajst-30235	74	16	score	score	NOUN
ajst-30235	74	17	resnet	resnet	NOUN
ajst-30235	74	18	0.8773	0.8773	NUM
ajst-30235	74	19	0.8658	0.8658	NUM
ajst-30235	74	20	0.8634	0.8634	NUM
ajst-30235	74	21	lstm	lstm	NOUN
ajst-30235	74	22	0.8926	0.8926	NUM
ajst-30235	74	23	0.8891	0.8891	NUM
ajst-30235	74	24	0.8825	0.8825	NUM
ajst-30235	74	25	cnn	cnn	PROPN
ajst-30235	74	26	0.9039	0.9039	NUM
ajst-30235	74	27	0.8948	0.8948	NUM
ajst-30235	74	28	0.8961	0.8961	NUM
ajst-30235	74	29	se	se	PROPN
ajst-30235	74	30	-	-	PROPN
ajst-30235	74	31	cnn	cnn	PROPN
ajst-30235	74	32	0.9263	0.9263	NUM
ajst-30235	74	33	0.9235	0.9235	NUM
ajst-30235	74	34	0.9219	0.9219	NUM
ajst-30235	74	35	it	it	PRON
ajst-30235	74	36	can	can	AUX
ajst-30235	74	37	be	be	AUX
ajst-30235	74	38	learned	learn	VERB
ajst-30235	74	39	that	that	SCONJ
ajst-30235	74	40	resnet	resnet	NOUN
ajst-30235	74	41	performs	perform	VERB
ajst-30235	74	42	relatively	relatively	ADV
ajst-30235	74	43	weakly	weakly	ADJ
ajst-30235	74	44	in	in	ADP
ajst-30235	74	45	the	the	DET
ajst-30235	74	46	bearing	bear	VERB
ajst-30235	74	47	fault	fault	NOUN
ajst-30235	74	48	diagnosis	diagnosis	NOUN
ajst-30235	74	49	task	task	NOUN
ajst-30235	74	50	,	,	PUNCT
ajst-30235	74	51	its	its	PRON
ajst-30235	74	52	precision	precision	NOUN
ajst-30235	74	53	and	and	CCONJ
ajst-30235	74	54	recall	recall	NOUN
ajst-30235	74	55	are	be	AUX
ajst-30235	74	56	low	low	ADJ
ajst-30235	74	57	,	,	PUNCT
ajst-30235	74	58	and	and	CCONJ
ajst-30235	74	59	its	its	PRON
ajst-30235	74	60	f1	f1	NOUN
ajst-30235	74	61	-	-	PUNCT
ajst-30235	74	62	score	score	NOUN
ajst-30235	74	63	is	be	AUX
ajst-30235	74	64	also	also	ADV
ajst-30235	74	65	at	at	ADP
ajst-30235	74	66	a	a	DET
ajst-30235	74	67	low	low	ADJ
ajst-30235	74	68	level.lstm	level.lstm	NOUN
ajst-30235	74	69	performs	perform	NOUN
ajst-30235	74	70	well	well	ADV
ajst-30235	74	71	in	in	ADP
ajst-30235	74	72	capturing	capture	VERB
ajst-30235	74	73	the	the	DET
ajst-30235	74	74	long	long	ADJ
ajst-30235	74	75	term	term	NOUN
ajst-30235	74	76	dependencies	dependency	NOUN
ajst-30235	74	77	of	of	ADP
ajst-30235	74	78	the	the	DET
ajst-30235	74	79	time	time	NOUN
ajst-30235	74	80	series	series	PROPN
ajst-30235	74	81	data	data	PROPN
ajst-30235	74	82	,	,	PUNCT
ajst-30235	74	83	and	and	CCONJ
ajst-30235	74	84	thus	thus	ADV
ajst-30235	74	85	can	can	AUX
ajst-30235	74	86	effectively	effectively	ADV
ajst-30235	74	87	identify	identify	VERB
ajst-30235	74	88	the	the	DET
ajst-30235	74	89	fault	fault	NOUN
ajst-30235	74	90	features	feature	VERB
ajst-30235	74	91	in	in	ADP
ajst-30235	74	92	the	the	DET
ajst-30235	74	93	bearing	bearing	NOUN
ajst-30235	74	94	vibration	vibration	NOUN
ajst-30235	74	95	signals.the	signals.the	DET
ajst-30235	74	96	performance	performance	NOUN
ajst-30235	74	97	of	of	ADP
ajst-30235	74	98	lstm	lstm	NOUN
ajst-30235	74	99	is	be	AUX
ajst-30235	74	100	better	well	ADJ
ajst-30235	74	101	compared	compare	VERB
ajst-30235	74	102	to	to	ADP
ajst-30235	74	103	that	that	PRON
ajst-30235	74	104	of	of	ADP
ajst-30235	74	105	resnet	resnet	NOUN
ajst-30235	74	106	in	in	ADP
ajst-30235	74	107	this	this	DET
ajst-30235	74	108	experiment	experiment	NOUN
ajst-30235	74	109	,	,	PUNCT
ajst-30235	74	110	but	but	CCONJ
ajst-30235	74	111	it	it	PRON
ajst-30235	74	112	is	be	AUX
ajst-30235	74	113	still	still	ADV
ajst-30235	74	114	not	not	PART
ajst-30235	74	115	as	as	ADV
ajst-30235	74	116	good	good	ADJ
ajst-30235	74	117	as	as	ADP
ajst-30235	74	118	that	that	PRON
ajst-30235	74	119	of	of	ADP
ajst-30235	74	120	the	the	DET
ajst-30235	74	121	cnn	cnn	PROPN
ajst-30235	74	122	model	model	NOUN
ajst-30235	74	123	and	and	CCONJ
ajst-30235	74	124	se	se	PROPN
ajst-30235	74	125	-	-	PROPN
ajst-30235	74	126	cnn	cnn	PROPN
ajst-30235	74	127	model	model	NOUN
ajst-30235	74	128	.	.	PUNCT
ajst-30235	75	1	and	and	CCONJ
ajst-30235	75	2	although	although	SCONJ
ajst-30235	75	3	the	the	DET
ajst-30235	75	4	original	original	ADJ
ajst-30235	75	5	cnn	cnn	NOUN
ajst-30235	75	6	model	model	NOUN
ajst-30235	75	7	has	have	VERB
ajst-30235	75	8	good	good	ADJ
ajst-30235	75	9	classification	classification	NOUN
ajst-30235	75	10	performance	performance	NOUN
ajst-30235	75	11	in	in	ADP
ajst-30235	75	12	this	this	DET
ajst-30235	75	13	experimental	experimental	ADJ
ajst-30235	75	14	task	task	NOUN
ajst-30235	75	15	,	,	PUNCT
ajst-30235	75	16	it	it	PRON
ajst-30235	75	17	is	be	AUX
ajst-30235	75	18	still	still	ADV
ajst-30235	75	19	slightly	slightly	ADV
ajst-30235	75	20	inferior	inferior	ADJ
ajst-30235	75	21	to	to	ADP
ajst-30235	75	22	the	the	DET
ajst-30235	75	23	se	se	PROPN
ajst-30235	75	24	-	-	PROPN
ajst-30235	75	25	cnn	cnn	PROPN
ajst-30235	75	26	model	model	NOUN
ajst-30235	75	27	,	,	PUNCT
ajst-30235	75	28	which	which	PRON
ajst-30235	75	29	enhances	enhance	VERB
ajst-30235	75	30	the	the	DET
ajst-30235	75	31	selective	selective	ADJ
ajst-30235	75	32	expression	expression	NOUN
ajst-30235	75	33	of	of	ADP
ajst-30235	75	34	features	feature	NOUN
ajst-30235	75	35	by	by	ADP
ajst-30235	75	36	introducing	introduce	VERB
ajst-30235	75	37	the	the	DET
ajst-30235	75	38	se	se	PROPN
ajst-30235	75	39	module	module	NOUN
ajst-30235	75	40	,	,	PUNCT
ajst-30235	75	41	effectively	effectively	ADV
ajst-30235	75	42	reduces	reduce	VERB
ajst-30235	75	43	the	the	DET
ajst-30235	75	44	rate	rate	NOUN
ajst-30235	75	45	of	of	ADP
ajst-30235	75	46	misclassification	misclassification	NOUN
ajst-30235	75	47	and	and	CCONJ
ajst-30235	75	48	omission	omission	NOUN
ajst-30235	75	49	,	,	PUNCT
ajst-30235	75	50	and	and	CCONJ
ajst-30235	75	51	shows	show	VERB
ajst-30235	75	52	better	well	ADJ
ajst-30235	75	53	robustness	robustness	NOUN
ajst-30235	75	54	,	,	PUNCT
ajst-30235	75	55	especially	especially	ADV
ajst-30235	75	56	in	in	ADP
ajst-30235	75	57	the	the	DET
ajst-30235	75	58	case	case	NOUN
ajst-30235	75	59	of	of	ADP
ajst-30235	75	60	category	category	NOUN
ajst-30235	75	61	imbalance	imbalance	NOUN
ajst-30235	75	62	.	.	PUNCT
ajst-30235	76	1	4	4	X
ajst-30235	76	2	.	.	X
ajst-30235	76	3	conclusion	conclusion	NOUN
ajst-30235	76	4	in	in	ADP
ajst-30235	76	5	this	this	DET
ajst-30235	76	6	paper	paper	NOUN
ajst-30235	76	7	,	,	PUNCT
ajst-30235	76	8	a	a	DET
ajst-30235	76	9	bearing	bear	VERB
ajst-30235	76	10	fault	fault	NOUN
ajst-30235	76	11	diagnosis	diagnosis	NOUN
ajst-30235	76	12	method	method	NOUN
ajst-30235	76	13	based	base	VERB
ajst-30235	76	14	on	on	ADP
ajst-30235	76	15	secnn	secnn	PROPN
ajst-30235	76	16	is	be	AUX
ajst-30235	76	17	proposed	propose	VERB
ajst-30235	76	18	,	,	PUNCT
ajst-30235	76	19	which	which	PRON
ajst-30235	76	20	enhances	enhance	VERB
ajst-30235	76	21	the	the	DET
ajst-30235	76	22	feature	feature	NOUN
ajst-30235	76	23	extraction	extraction	NOUN
ajst-30235	76	24	capability	capability	NOUN
ajst-30235	76	25	of	of	ADP
ajst-30235	76	26	convolutional	convolutional	ADJ
ajst-30235	76	27	neural	neural	ADJ
ajst-30235	76	28	network	network	NOUN
ajst-30235	76	29	in	in	ADP
ajst-30235	76	30	bearing	bear	VERB
ajst-30235	76	31	vibration	vibration	NOUN
ajst-30235	76	32	signal	signal	NOUN
ajst-30235	76	33	analysis	analysis	NOUN
ajst-30235	76	34	by	by	ADP
ajst-30235	76	35	introducing	introduce	VERB
ajst-30235	76	36	the	the	DET
ajst-30235	76	37	se	se	PROPN
ajst-30235	76	38	module	module	NOUN
ajst-30235	76	39	to	to	PART
ajst-30235	76	40	adaptively	adaptively	ADV
ajst-30235	76	41	adjust	adjust	VERB
ajst-30235	76	42	the	the	DET
ajst-30235	76	43	weights	weight	NOUN
ajst-30235	76	44	of	of	ADP
ajst-30235	76	45	channel	channel	NOUN
ajst-30235	76	46	features	feature	NOUN
ajst-30235	76	47	.	.	PUNCT
ajst-30235	77	1	experimental	experimental	ADJ
ajst-30235	77	2	results	result	NOUN
ajst-30235	77	3	show	show	VERB
ajst-30235	77	4	that	that	SCONJ
ajst-30235	77	5	se	se	PROPN
ajst-30235	77	6	-	-	NOUN
ajst-30235	77	7	cnn	cnn	PROPN
ajst-30235	77	8	has	have	VERB
ajst-30235	77	9	higher	high	ADJ
ajst-30235	77	10	precision	precision	NOUN
ajst-30235	77	11	,	,	PUNCT
ajst-30235	77	12	recall	recall	NOUN
ajst-30235	77	13	and	and	CCONJ
ajst-30235	77	14	f1	f1	NOUN
ajst-30235	77	15	-	-	PUNCT
ajst-30235	77	16	score	score	NOUN
ajst-30235	77	17	in	in	ADP
ajst-30235	77	18	the	the	DET
ajst-30235	77	19	bearing	bear	VERB
ajst-30235	77	20	fault	fault	NOUN
ajst-30235	77	21	diagnosis	diagnosis	NOUN
ajst-30235	77	22	task	task	NOUN
ajst-30235	77	23	compared	compare	VERB
ajst-30235	77	24	with	with	ADP
ajst-30235	77	25	traditional	traditional	ADJ
ajst-30235	77	26	resnet	resnet	NOUN
ajst-30235	77	27	,	,	PUNCT
ajst-30235	77	28	lstm	lstm	NOUN
ajst-30235	77	29	and	and	CCONJ
ajst-30235	77	30	cnn	cnn	PROPN
ajst-30235	77	31	models	model	NOUN
ajst-30235	77	32	,	,	PUNCT
ajst-30235	77	33	and	and	CCONJ
ajst-30235	77	34	exhibits	exhibit	VERB
ajst-30235	77	35	better	well	ADJ
ajst-30235	77	36	robustness	robustness	NOUN
ajst-30235	77	37	especially	especially	ADV
ajst-30235	77	38	in	in	ADP
ajst-30235	77	39	the	the	DET
ajst-30235	77	40	case	case	NOUN
ajst-30235	77	41	of	of	ADP
ajst-30235	77	42	category	category	NOUN
ajst-30235	77	43	imbalance	imbalance	NOUN
ajst-30235	77	44	.	.	PUNCT
ajst-30235	78	1	compared	compare	VERB
ajst-30235	78	2	with	with	ADP
ajst-30235	78	3	the	the	DET
ajst-30235	78	4	other	other	ADJ
ajst-30235	78	5	models	model	NOUN
ajst-30235	78	6	,	,	PUNCT
ajst-30235	78	7	resnet	resnet	NOUN
ajst-30235	78	8	performs	perform	VERB
ajst-30235	78	9	less	less	ADV
ajst-30235	78	10	well	well	ADV
ajst-30235	78	11	in	in	ADP
ajst-30235	78	12	fault	fault	NOUN
ajst-30235	78	13	diagnosis	diagnosis	NOUN
ajst-30235	78	14	,	,	PUNCT
ajst-30235	78	15	and	and	CCONJ
ajst-30235	78	16	lstm	lstm	NOUN
ajst-30235	78	17	captures	capture	NOUN
ajst-30235	78	18	timing	time	VERB
ajst-30235	78	19	information	information	NOUN
ajst-30235	78	20	better	well	ADV
ajst-30235	78	21	but	but	CCONJ
ajst-30235	78	22	still	still	ADV
ajst-30235	78	23	not	not	PART
ajst-30235	78	24	as	as	ADV
ajst-30235	78	25	good	good	ADJ
ajst-30235	78	26	as	as	ADP
ajst-30235	78	27	cnn	cnn	PROPN
ajst-30235	78	28	and	and	CCONJ
ajst-30235	78	29	secnn.the	secnn.the	DET
ajst-30235	78	30	primitive	primitive	ADJ
ajst-30235	78	31	cnn	cnn	PROPN
ajst-30235	78	32	has	have	VERB
ajst-30235	78	33	good	good	ADJ
ajst-30235	78	34	classification	classification	NOUN
ajst-30235	78	35	performance	performance	NOUN
ajst-30235	78	36	but	but	CCONJ
ajst-30235	78	37	there	there	PRON
ajst-30235	78	38	is	be	VERB
ajst-30235	78	39	still	still	ADV
ajst-30235	78	40	room	room	NOUN
ajst-30235	78	41	for	for	ADP
ajst-30235	78	42	improvement	improvement	NOUN
ajst-30235	78	43	in	in	ADP
ajst-30235	78	44	feature	feature	NOUN
ajst-30235	78	45	selectivity.se	selectivity.se	PROPN
ajst-30235	78	46	-	-	PUNCT
ajst-30235	78	47	cnn	cnn	PROPN
ajst-30235	78	48	,	,	PUNCT
ajst-30235	78	49	by	by	ADP
ajst-30235	78	50	introducing	introduce	VERB
ajst-30235	78	51	the	the	DET
ajst-30235	78	52	channel	channel	NOUN
ajst-30235	78	53	attention	attention	NOUN
ajst-30235	78	54	mechanism	mechanism	NOUN
ajst-30235	78	55	,	,	PUNCT
ajst-30235	78	56	significantly	significantly	ADV
ajst-30235	78	57	improves	improve	VERB
ajst-30235	78	58	the	the	DET
ajst-30235	78	59	ability	ability	NOUN
ajst-30235	78	60	of	of	ADP
ajst-30235	78	61	capturing	capture	VERB
ajst-30235	78	62	key	key	ADJ
ajst-30235	78	63	signal	signal	NOUN
ajst-30235	78	64	features	feature	NOUN
ajst-30235	78	65	and	and	CCONJ
ajst-30235	78	66	optimizes	optimize	VERB
ajst-30235	78	67	the	the	DET
ajst-30235	78	68	diagnosis	diagnosis	NOUN
ajst-30235	78	69	accuracy	accuracy	NOUN
ajst-30235	78	70	.	.	PUNCT
ajst-30235	79	1	references	reference	NOUN
ajst-30235	79	2	[	[	X
ajst-30235	79	3	1	1	NUM
ajst-30235	79	4	]	]	X
ajst-30235	79	5	zhang	zhang	PROPN
ajst-30235	79	6	x	x	PUNCT
ajst-30235	79	7	l.	l.	PROPN
ajst-30235	79	8	discussion	discussion	NOUN
ajst-30235	79	9	on	on	ADP
ajst-30235	79	10	the	the	DET
ajst-30235	79	11	acquisition	acquisition	NOUN
ajst-30235	79	12	and	and	CCONJ
ajst-30235	79	13	processing	processing	NOUN
ajst-30235	79	14	of	of	ADP
ajst-30235	79	15	motor	motor	NOUN
ajst-30235	79	16	bearing	bear	VERB
ajst-30235	79	17	vibration	vibration	NOUN
ajst-30235	79	18	signals[j	signals[j	PROPN
ajst-30235	79	19	]	]	PUNCT
ajst-30235	79	20	.	.	PUNCT
ajst-30235	80	1	explosion	explosion	NOUN
ajst-30235	80	2	-	-	PUNCT
ajst-30235	80	3	proof	proof	ADJ
ajst-30235	80	4	electric	electric	ADJ
ajst-30235	80	5	machines	machine	NOUN
ajst-30235	80	6	,	,	PUNCT
ajst-30235	80	7	2024	2024	NUM
ajst-30235	80	8	,	,	PUNCT
ajst-30235	80	9	59(04	59(04	NUM
ajst-30235	80	10	):	):	PUNCT
ajst-30235	80	11	87	87	NUM
ajst-30235	80	12	-	-	SYM
ajst-30235	80	13	90	90	NUM
ajst-30235	80	14	.	.	PUNCT
ajst-30235	81	1	[	[	X
ajst-30235	81	2	2	2	NUM
ajst-30235	81	3	]	]	X
ajst-30235	81	4	zhao	zhao	PROPN
ajst-30235	81	5	l	l	PROPN
ajst-30235	81	6	,	,	PUNCT
ajst-30235	81	7	meng	meng	PROPN
ajst-30235	81	8	y	y	PROPN
ajst-30235	81	9	,	,	PUNCT
ajst-30235	81	10	jiang	jiang	PROPN
ajst-30235	81	11	z	z	PROPN
ajst-30235	81	12	l	l	PROPN
ajst-30235	81	13	,	,	PUNCT
ajst-30235	81	14	et	et	PROPN
ajst-30235	81	15	al	al	PROPN
ajst-30235	81	16	.	.	PROPN
ajst-30235	81	17	bearing	bear	VERB
ajst-30235	81	18	fault	fault	NOUN
ajst-30235	81	19	diagnosis	diagnosis	NOUN
ajst-30235	81	20	based	base	VERB
ajst-30235	81	21	on	on	ADP
ajst-30235	81	22	wavelet	wavelet	NOUN
ajst-30235	81	23	transform	transform	NOUN
ajst-30235	81	24	and	and	CCONJ
ajst-30235	81	25	attention	attention	NOUN
ajst-30235	81	26	mechanism[j	mechanism[j	PROPN
ajst-30235	81	27	/	/	SYM
ajst-30235	81	28	ol	ol	ADJ
ajst-30235	81	29	]	]	PUNCT
ajst-30235	81	30	.	.	PUNCT
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ajst-30235	88	1	https://doi.org/10.20040/j.cnki.1000-7709.2025.20240783	https://doi.org/10.20040/j.cnki.1000-7709.2025.20240783	NOUN
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ajst-30235	92	7	,	,	PUNCT
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ajst-30235	92	9	):	):	PUNCT
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ajst-30235	109	6	-	-	SYM
ajst-30235	109	7	7141	7141	NUM
ajst-30235	109	8	.	.	PUNCT
ajst-30235	110	1	[	[	X
ajst-30235	110	2	14	14	NUM
ajst-30235	110	3	]	]	X
ajst-30235	110	4	zhou	zhou	PROPN
ajst-30235	110	5	f	f	PROPN
ajst-30235	110	6	y	y	PROPN
ajst-30235	110	7	,	,	PUNCT
ajst-30235	110	8	jin	jin	NOUN
ajst-30235	110	9	l	l	PROPN
ajst-30235	110	10	p	p	X
ajst-30235	110	11	,	,	PUNCT
ajst-30235	110	12	dong	dong	PROPN
ajst-30235	110	13	j.	j.	PROPN
ajst-30235	110	14	a	a	DET
ajst-30235	110	15	review	review	NOUN
ajst-30235	110	16	of	of	ADP
ajst-30235	110	17	convolutional	convolutional	ADJ
ajst-30235	110	18	neural	neural	ADJ
ajst-30235	110	19	networks	network	NOUN
ajst-30235	110	20	[	[	X
ajst-30235	110	21	j	j	X
ajst-30235	110	22	]	]	X
ajst-30235	110	23	.	.	PUNCT
ajst-30235	111	1	journal	journal	PROPN
ajst-30235	111	2	of	of	ADP
ajst-30235	111	3	computer	computer	NOUN
ajst-30235	111	4	research	research	NOUN
ajst-30235	111	5	and	and	CCONJ
ajst-30235	111	6	development	development	NOUN
ajst-30235	111	7	,	,	PUNCT
ajst-30235	111	8	2017(6	2017(6	NUM
ajst-30235	111	9	):	):	PUNCT
ajst-30235	111	10	1229	1229	NUM
ajst-30235	111	11	-	-	SYM
ajst-30235	111	12	1251	1251	NUM
ajst-30235	111	13	.	.	PUNCT
ajst-30235	112	1	[	[	X
ajst-30235	112	2	15	15	NUM
ajst-30235	112	3	]	]	X
ajst-30235	112	4	zhang	zhang	PROPN
ajst-30235	112	5	d	d	PROPN
ajst-30235	112	6	,	,	PUNCT
ajst-30235	112	7	kong	kong	PROPN
ajst-30235	112	8	k	k	PROPN
ajst-30235	112	9	,	,	PUNCT
ajst-30235	112	10	zhu	zhu	PROPN
ajst-30235	112	11	c	c	X
ajst-30235	112	12	,	,	PUNCT
ajst-30235	112	13	et	et	PROPN
ajst-30235	112	14	al	al	PROPN
ajst-30235	112	15	.	.	PROPN
ajst-30235	112	16	bearing	bear	VERB
ajst-30235	112	17	remaining	remain	VERB
ajst-30235	112	18	useful	useful	ADJ
ajst-30235	112	19	life	life	NOUN
ajst-30235	112	20	prediction	prediction	NOUN
ajst-30235	112	21	based	base	VERB
ajst-30235	112	22	on	on	ADP
ajst-30235	112	23	cnn	cnn	PROPN
ajst-30235	112	24	-	-	PUNCT
ajst-30235	112	25	transformer	transformer	NOUN
ajst-30235	112	26	encoder	encoder	NOUN
ajst-30235	112	27	-	-	PUNCT
ajst-30235	112	28	bilstm	bilstm	NOUN
ajst-30235	112	29	model	model	NOUN
ajst-30235	113	1	[	[	X
ajst-30235	113	2	j	j	X
ajst-30235	113	3	/	/	SYM
ajst-30235	113	4	ol	ol	PROPN
ajst-30235	113	5	]	]	PUNCT
ajst-30235	113	6	.	.	PUNCT
ajst-30235	114	1	journal	journal	PROPN
ajst-30235	114	2	of	of	ADP
ajst-30235	114	3	huazhong	huazhong	PROPN
ajst-30235	114	4	university	university	PROPN
ajst-30235	114	5	of	of	ADP
ajst-30235	114	6	science	science	NOUN
ajst-30235	114	7	and	and	CCONJ
ajst-30235	114	8	technology	technology	NOUN
ajst-30235	114	9	(	(	PUNCT
ajst-30235	114	10	natural	natural	ADJ
ajst-30235	114	11	science	science	NOUN
ajst-30235	114	12	edition	edition	NOUN
ajst-30235	114	13	)	)	PUNCT
ajst-30235	114	14	,	,	PUNCT
ajst-30235	114	15	1	1	NUM
ajst-30235	114	16	-	-	SYM
ajst-30235	114	17	16	16	NUM
ajst-30235	114	18	[	[	X
ajst-30235	114	19	2025	2025	NUM
ajst-30235	114	20	-	-	SYM
ajst-30235	114	21	03	03	NUM
ajst-30235	114	22	-	-	SYM
ajst-30235	114	23	19	19	NUM
ajst-30235	114	24	]	]	PUNCT
ajst-30235	114	25	.	.	PUNCT
ajst-30235	115	1	https://doi.org/10.13245/j.hust.24091	https://doi.org/10.13245/j.hust.24091	PROPN
ajst-30235	115	2	.	.	PUNCT
ajst-30235	116	1	[	[	X
ajst-30235	116	2	16	16	NUM
ajst-30235	116	3	]	]	X
ajst-30235	116	4	chen	chen	PROPN
ajst-30235	116	5	y	y	PROPN
ajst-30235	116	6	,	,	PUNCT
ajst-30235	116	7	qu	qu	PROPN
ajst-30235	116	8	j	j	PROPN
ajst-30235	116	9	l	l	PROPN
ajst-30235	116	10	,	,	PUNCT
ajst-30235	116	11	wang	wang	PROPN
ajst-30235	116	12	x	x	PROPN
ajst-30235	117	1	f	f	X
ajst-30235	117	2	,	,	PUNCT
ajst-30235	117	3	et	et	PROPN
ajst-30235	117	4	al	al	PROPN
ajst-30235	117	5	.	.	PROPN
ajst-30235	118	1	cnn	cnn	PROPN
ajst-30235	118	2	-	-	PUNCT
ajst-30235	118	3	lstm	lstm	PROPN
ajst-30235	118	4	based	base	VERB
ajst-30235	118	5	rolling	roll	VERB
ajst-30235	118	6	bearing	bear	VERB
ajst-30235	118	7	fault	fault	NOUN
ajst-30235	118	8	diagnosis	diagnosis	NOUN
ajst-30235	118	9	method	method	NOUN
ajst-30235	118	10	with	with	ADP
ajst-30235	118	11	enhanced	enhanced	ADJ
ajst-30235	118	12	temporal	temporal	ADJ
ajst-30235	118	13	memory	memory	NOUN
ajst-30235	118	14	[	[	X
ajst-30235	118	15	j	j	X
ajst-30235	118	16	]	]	X
ajst-30235	118	17	.	.	PUNCT
ajst-30235	119	1	noise	noise	NOUN
ajst-30235	119	2	and	and	CCONJ
ajst-30235	119	3	vibration	vibration	NOUN
ajst-30235	119	4	control	control	NOUN
ajst-30235	119	5	,	,	PUNCT
ajst-30235	119	6	2025	2025	NUM
ajst-30235	119	7	,	,	PUNCT
ajst-30235	119	8	45(01	45(01	NUM
ajst-30235	119	9	):	):	PUNCT
ajst-30235	119	10	105111	105111	NUM
ajst-30235	119	11	.	.	PUNCT
ajst-30235	120	1	[	[	X
ajst-30235	120	2	17	17	NUM
ajst-30235	120	3	]	]	X
ajst-30235	120	4	sun	sun	PROPN
ajst-30235	120	5	y	y	PROPN
ajst-30235	120	6	,	,	PUNCT
ajst-30235	120	7	zhang	zhang	PROPN
ajst-30235	120	8	l	l	PROPN
ajst-30235	120	9	,	,	PUNCT
ajst-30235	120	10	zhou	zhou	PROPN
ajst-30235	120	11	k.	k.	PROPN
ajst-30235	120	12	research	research	PROPN
ajst-30235	120	13	on	on	ADP
ajst-30235	120	14	rolling	roll	VERB
ajst-30235	120	15	bearing	bear	VERB
ajst-30235	120	16	fault	fault	NOUN
ajst-30235	120	17	diagnosis	diagnosis	NOUN
ajst-30235	120	18	method	method	NOUN
ajst-30235	120	19	based	base	VERB
ajst-30235	120	20	on	on	ADP
ajst-30235	120	21	genetic	genetic	ADJ
ajst-30235	120	22	algorithm	algorithm	NOUN
ajst-30235	120	23	optimized	optimize	VERB
ajst-30235	120	24	convolutional	convolutional	ADJ
ajst-30235	120	25	neural	neural	ADJ
ajst-30235	120	26	network	network	NOUN
ajst-30235	121	1	[	[	X
ajst-30235	121	2	j	j	X
ajst-30235	121	3	]	]	X
ajst-30235	121	4	.	.	PUNCT
ajst-30235	122	1	manufacturing	manufacture	VERB
ajst-30235	122	2	automation	automation	NOUN
ajst-30235	122	3	,	,	PUNCT
ajst-30235	122	4	2025	2025	NUM
ajst-30235	122	5	,	,	PUNCT
ajst-30235	122	6	47(01	47(01	NUM
ajst-30235	122	7	):	):	PUNCT
ajst-30235	122	8	89	89	NUM
ajst-30235	122	9	-	-	SYM
ajst-30235	122	10	95	95	NUM
ajst-30235	122	11	.	.	PUNCT