id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ajst-29929	Yuan, Xun; Wu, Wei	A Bearing Fault Diagnosis Method Based on Fusion of CNN-BiLSTM-Transformer and Cross-Attention	2025	9	.pdf	application/pdf	4149	225	43	Abstract: To address the limitations of traditional diagnostic models in achieving high accuracy in rolling bearing fault diagnosis and their inadequate extraction of vibration signal features across both frequency and time domains, this paper introduces a fault diagnosis approach that integrates multiple neural networks with a cross-attention mechanism. The method employs Fast Fourier Transform (FFT) and Variational Mode Decomposition (VMD) to extract time- frequency domain features from the signals, enabling the extraction of multi-scale features from fault signals.	cache/ajst-29929.pdf	txt/ajst-29929.txt