ISSN: 2180-1053 Vol. 2 No. 1 January-June 2010 Image Classification of Temperature Distribution Using Fourier Series Strategy 11 Image ClassIfICatIon of temperature DIstrIbutIon usIng fourIer serIes strategy m.a.salim1, a. r. m. rosdzimin2, K.osman3, a.noordin4, m.a.mohd rosli5 1,5Faculty of Mechanical Engineering, Universiti Teknikal Malaysia Melaka, Karung Berkunci 1752, Pejabat Pos Durian Tunggal, 76109 Durian Tunggal, Melaka, Malaysia. 2Department of Mechanical, Faculty of Engineering, Universiti Pertahanan Nasional Malaysia, Kem Sungai Besi, 57000 Kuala Lumpur, Malaysia. 3Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor Bahru, Johor, Malaysia. 4Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Karung Berkunci 1752, Pejabat Pos Durian Tunggal, 76109 Durian Tunggal, Melaka, Malaysia. Email: 1azli@utem.edu.my, 2rosdzimin@upnm.edu.my, 3kahar@fkm.utm.my, 4aminurrashid@ utem.edu.my, 5afzanizam@utem.edu.my ABSTRACT This paper presents the analysis of temperature distribution by using Fourier series strategy. Using this strategy, two analyses have been made where an even and odd number is applied in the series. In even number, the trivial solution occur where there are no solution been made, but in odd number the solution is succeed. By using the equation made by odd number, the equation has been analysis using MatLab-Programming. In this analysis, the contour mapping of temperature distribution is shown clearly. Based on the mapping, it can be concluded that the temperature distribution happens because of the adiabatic phenomenon of the material properties itself. KEYWORDS: Fourier series, Isotherms, Adiabatic, Temperature distribution. 1.0 IntroDuCtIon It is not easy to give an exact definition of temperature because ISSN: 2180-1053 Vol. 2 No. 1 January-June 2010 Journal of Mechanical Engineering and Technology 12 majority of human around the world classify temperature to only familiar with hotness or coldness. In physiological ambiance, the level of temperature can be measured as a cold, freezing cold, warm, hot and red hot. For the basic example, metal will feel much colder than the wood when both materials are at the same temperature and same place. According to this example, several materials properties can be changed regarding the changes of the temperature around the material itself. The material properties can be changed with temperature in a repeatable and predictable way according the basis of accurate temperature measurement. In a common example, a cup of hot tea present on the table ultimately cools off and cold drink sooner or later warms up. In this phenomenon, a body of hot tea and cold drink are brought into contact with another body with different temperature and heat transfer phenomenon is happen where the hot temperature transfer it temperature to the low temperature areas. This phenomenon will continue until both area reach with same temperature. When both areas are in a same temperature, these two areas are said in a thermal equilibrium condition. Zeroth Law of Thermodynamics explains that if two bodies in thermal equilibrium with a third body, they are also in thermal equilibrium for each others. This law had been formulated by R.H.Fowler in 1931. In this study, the authors have studied the mediums’ properties according to the heat transfer effect in several materials. Therefore, the knowledge on medium’s value of temperature at all point is necessary. Heat transfer analysis basically plays a central role in the design of chemical processes and in the development of process system. In order to make accurate analysis to the heat transfer problem, parameters such as the roll speed, thermal conductivity, rate of cold air, thickness and temperature surface is needed. Heat transfer problem can occur by three mechanisms and there are conduction, convection and radiation. Conduction mechanism is a collision of molecules causes the thermal energy to be transferred from one molecule to other one molecule. In this heat transfer process, the very energetic molecules will lose their energy while the lower energy molecules will get the more energy. In convection mechanism, it only occurs when the energy in macroscopic flow in fluid was associated with a parcel. Then, the fluid was converted to another region of space. In this case, it also can be called as an unsteady state behaviour. The radiation mechanism happens when the molecular vibrate and give an electromagnet radiation which certain amount to the other molecular. The radiation behaviour transmits the energy throughout the space ISSN: 2180-1053 Vol. 2 No. 1 January-June 2010 Image Classification of Temperature Distribution Using Fourier Series Strategy 13 and vacuum containing. These three mechanisms have a potential to generate the instantaneous values of temperature at all points of the medium of interest and also called as a temperature distribution or field. The unsteady temperature distribution appears when medium’s temperature not only varies from point to point, but also depends on time. In time domain, the temperature at a various points in a medium can be changed and then the internal energy of the molecular also changed. A steady state temperature distribution occurs when a temperature at a given point never varies with time and this type is called as a space coordinates only. The temperature distribution by governing equations also called a three dimensional. This equation of temperature is describes as a function of three space coordinates, temperature, these two areas are said in a thermal equilibrium condition. Zeroth Law of Thermodynamics explains that if two bodies in thermal equilibrium with a third body, they are also in thermal equilibrium for each others. This law had been formulated by R.H.Fowler in 1931. In this study, the authors have studied the mediums’ properties according to the heat transfer effect in several materials. Therefore, the knowledge on medium’s value of temperature at all point is necessary. Heat transfer analysis basically plays a central role in the design of chemical processes and in the development of process system. In order to make accurate analysis to the heat transfer problem, parameters such as the roll speed, thermal conductivity, rate of cold air, thickness and temperature surface is needed. Heat transfer problem can occur by three mechanisms and there are conduction, convection and radiation. Conduction mechanism is a collision of molecules causes the thermal energy to be transferred from one molecule to other one molecule. In this heat transfer process, the very energetic molecules will lose their energy while the lower energy molecules will get the more energy. In convection mechanism, it only occurs when the energy in macroscopic flow in fluid was associated with a parcel. Then, the fluid was converted to another region of space. In this case, it also can be called as an unsteady state behaviour. The radiation mechanism happens when the molecular vibrate and give an electromagnet radiation which certain amount to the other molecular. The radiation behaviour transmits the energy throughout the space and vacuum containing. These three mechanisms have a potential to generate the instantaneous values of temperature at all points of the medium of interest and also called as a temperature distribution or field. The unsteady temperature distribution appears when medium’s temperature not only varies from point to point, but also depends on time. In time domain, the temperature at a various points in a medium can be changed and then the internal energy of the molecular also changed. A steady state temperature distribution occurs when a temperature at a given point never varies with time and this type is called as a space coordinates only. The temperature distribution by governing equations also called a three dimensional. This equation of temperature is describes as a function of three space coordinates, . Therefore, if the points of a medium with equal temperatures are connected, the resulting surfaces are called isothermal surfaces. This intersection of isothermal surfaces with a plane yields a family of isotherms on the place surface. Important to note that the two isothermal surfaces never cut each other since there are no part of the medium can have two different temperatures at the same time, respectively (Kreysig, 2006), (Howard et al., 2003). Fourier series of all dimension is a general type of summation process under which the convergence or non-convergence of the corresponding partial sums at a given point depend only on the behaviour of the function at given point, and that continuity of the function at the point is sufficient for convergence (Bochner, 1935). Fourier series has been used for solving many heat transfer problems. Maria and Power (2000) was developed an efficient BEM scheme for the numerical solution of two-dimensional heat problems. The double Fourier series was rewritten using Green function that obtained by the images method. The double Fourier series is use in the domain integral of the integral representation formula to transform such integral into equivalent surface integrals. Maksimovich and Tsybul''skii (2004) determined nonstationary nonaxisymmetric temperature fields in bodies of revolution appearing on heating by internal heat sources through and due to convective heat exchange with an external medium. The solution of the problem is represented in the form of a Fourier series in an angular coordinate with coefficients being determined by a method of boundary elements. . Therefore, if the points of a medium with equal temperatures are connected, the resulting surfaces are called isothermal surfaces. This intersection of isothermal surfaces with a plane yields a family of isotherms on the place surface. Important to note that the two isothermal surfaces never cut each other since there are no part of the medium can have two different temperatures at the same time, respectively (Kreysig, 2006), (Howard et al., 2003). Fourier series of all dimension is a general type of summation process under which the convergence or non-convergence of the corresponding partial sums at a given point depend only on the behaviour of the function at given point, and that continuity of the function at the point is sufficient for convergence (Bochner, 1935). Fourier series has been used for solving many heat transfer problems. Maria and Power (2000) was developed an efficient BEM scheme for the numerical solution of two-dimensional heat problems. The double Fourier series was rewritten using Green function that obtained by the images method. The double Fourier series is use in the domain integral of the integral representation formula to transform such integral into equivalent surface integrals. Maksimovich and Tsybul’’skii (2004) determined nonstationary nonaxisymmetric temperature fields in bodies of revolution appearing on heating by internal heat sources through and due to convective heat exchange with an external medium. The solution of the problem is represented in the form of a Fourier series in an angular coordinate with coefficients being determined by a method of boundary elements. ISSN: 2180-1053 Vol. 2 No. 1 January-June 2010 Journal of Mechanical Engineering and Technology 14 2.0 fourIer serIes strategy Fourier series is a one method to analyze the periodic phenomenon and they occur quite frequently in engineering and elsewhere such as in rotating of machines, alternating electric currents or the motions of planets. Fourier series is also called as a Trigonometric series and it represent in periodic functions. The function on trigonometric can be defined from 2.0 FOURIER SERIES STRATEGY Fourier series is a one method to analyze the periodic phenomenon and they occur quite frequently in engineering and elsewhere such as in rotating of machines, alternating electric currents or the motions of planets. Fourier series is also called as a Trigonometric series and it represent in periodic functions. The function on trigonometric can be defined from , and has a period of of if for all values of x. According to the definition of the periodic, most practical situations such as a function can be expressed as a complex Fourier series like (Kreysig, 2006), (Black, 2008): The number is called as complex coefficients periodic functions. It can be compute by the integration as: This Fourier series also can be written as sine and cosine function. The new equation of this Fourier series represents as a: By the denoting the equation: Yields: This series is called a Fourier sine-cosine expansion. For this case, for all values of j, which it is, implies that must be real and then: Suppose that, Fourier series expansion for a more general function of and having a period of p instead of . Then, the new function can be introduced by: and has a period of 2.0 FOURIER SERIES STRATEGY Fourier series is a one method to analyze the periodic phenomenon and they occur quite frequently in engineering and elsewhere such as in rotating of machines, alternating electric currents or the motions of planets. Fourier series is also called as a Trigonometric series and it represent in periodic functions. The function on trigonometric can be defined from , and has a period of of if for all values of x. According to the definition of the periodic, most practical situations such as a function can be expressed as a complex Fourier series like (Kreysig, 2006), (Black, 2008): The number is called as complex coefficients periodic functions. It can be compute by the integration as: This Fourier series also can be written as sine and cosine function. The new equation of this Fourier series represents as a: By the denoting the equation: Yields: This series is called a Fourier sine-cosine expansion. For this case, for all values of j, which it is, implies that must be real and then: Suppose that, Fourier series expansion for a more general function of and having a period of p instead of . Then, the new function can be introduced by: for all values of x. According to the definition of the periodic, most practical situations such as a function can be expressed as a complex Fourier series like (Kreysig, 2006), (Black, 2008): 2.0 FOURIER SERIES STRATEGY Fourier series is a one method to analyze the periodic phenomenon and they occur quite frequently in engineering and elsewhere such as in rotating of machines, alternating electric currents or the motions of planets. Fourier series is also called as a Trigonometric series and it represent in periodic functions. The function on trigonometric can be defined from , and has a period of of if for all values of x. According to the definition of the periodic, most practical situations such as a function can be expressed as a complex Fourier series like (Kreysig, 2006), (Black, 2008): The number is called as complex coefficients periodic functions. It can be compute by the integration as: This Fourier series also can be written as sine and cosine function. The new equation of this Fourier series represents as a: By the denoting the equation: Yields: This series is called a Fourier sine-cosine expansion. For this case, for all values of j, which it is, implies that must be real and then: Suppose that, Fourier series expansion for a more general function of and having a period of p instead of . Then, the new function can be introduced by: The number is called as complex coefficients periodic functions. It can be compute by the integration as: 2.0 FOURIER SERIES STRATEGY Fourier series is a one method to analyze the periodic phenomenon and they occur quite frequently in engineering and elsewhere such as in rotating of machines, alternating electric currents or the motions of planets. Fourier series is also called as a Trigonometric series and it represent in periodic functions. The function on trigonometric can be defined from , and has a period of of if for all values of x. According to the definition of the periodic, most practical situations such as a function can be expressed as a complex Fourier series like (Kreysig, 2006), (Black, 2008): The number is called as complex coefficients periodic functions. It can be compute by the integration as: This Fourier series also can be written as sine and cosine function. The new equation of this Fourier series represents as a: By the denoting the equation: Yields: This series is called a Fourier sine-cosine expansion. For this case, for all values of j, which it is, implies that must be real and then: Suppose that, Fourier series expansion for a more general function of and having a period of p instead of . Then, the new function can be introduced by: This Fourier series also can be written as sine and cosine function. The new equation of this Fourier series represents as a: 2.0 FOURIER SERIES STRATEGY Fourier series is a one method to analyze the periodic phenomenon and they occur quite frequently in engineering and elsewhere such as in rotating of machines, alternating electric currents or the motions of planets. Fourier series is also called as a Trigonometric series and it represent in periodic functions. The function on trigonometric can be defined from , and has a period of of if for all values of x. According to the definition of the periodic, most practical situations such as a function can be expressed as a complex Fourier series like (Kreysig, 2006), (Black, 2008): The number is called as complex coefficients periodic functions. It can be compute by the integration as: This Fourier series also can be written as sine and cosine function. The new equation of this Fourier series represents as a: By the denoting the equation: Yields: This series is called a Fourier sine-cosine expansion. For this case, for all values of j, which it is, implies that must be real and then: Suppose that, Fourier series expansion for a more general function of and having a period of p instead of . Then, the new function can be introduced by: By the denoting the equation: 2.0 FOURIER SERIES STRATEGY Fourier series is a one method to analyze the periodic phenomenon and they occur quite frequently in engineering and elsewhere such as in rotating of machines, alternating electric currents or the motions of planets. Fourier series is also called as a Trigonometric series and it represent in periodic functions. The function on trigonometric can be defined from , and has a period of of if for all values of x. According to the definition of the periodic, most practical situations such as a function can be expressed as a complex Fourier series like (Kreysig, 2006), (Black, 2008): The number is called as complex coefficients periodic functions. It can be compute by the integration as: This Fourier series also can be written as sine and cosine function. The new equation of this Fourier series represents as a: By the denoting the equation: Yields: This series is called a Fourier sine-cosine expansion. For this case, for all values of j, which it is, implies that must be real and then: Suppose that, Fourier series expansion for a more general function of and having a period of p instead of . Then, the new function can be introduced by: Yields: 2.0 FOURIER SERIES STRATEGY Fourier series is a one method to analyze the periodic phenomenon and they occur quite frequently in engineering and elsewhere such as in rotating of machines, alternating electric currents or the motions of planets. Fourier series is also called as a Trigonometric series and it represent in periodic functions. The function on trigonometric can be defined from , and has a period of of if for all values of x. According to the definition of the periodic, most practical situations such as a function can be expressed as a complex Fourier series like (Kreysig, 2006), (Black, 2008): The number is called as complex coefficients periodic functions. It can be compute by the integration as: This Fourier series also can be written as sine and cosine function. The new equation of this Fourier series represents as a: By the denoting the equation: Yields: This series is called a Fourier sine-cosine expansion. For this case, for all values of j, which it is, implies that must be real and then: Suppose that, Fourier series expansion for a more general function of and having a period of p instead of . Then, the new function can be introduced by: This series is called a Fourier sine-cosine expansion. For this case, 2.0 FOURIER SERIES STRATEGY Fourier series is a one method to analyze the periodic phenomenon and they occur quite frequently in engineering and elsewhere such as in rotating of machines, alternating electric currents or the motions of planets. Fourier series is also called as a Trigonometric series and it represent in periodic functions. The function on trigonometric can be defined from , and has a period of of if for all values of x. According to the definition of the periodic, most practical situations such as a function can be expressed as a complex Fourier series like (Kreysig, 2006), (Black, 2008): The number is called as complex coefficients periodic functions. It can be compute by the integration as: This Fourier series also can be written as sine and cosine function. The new equation of this Fourier series represents as a: By the denoting the equation: Yields: This series is called a Fourier sine-cosine expansion. For this case, for all values of j, which it is, implies that must be real and then: Suppose that, Fourier series expansion for a more general function of and having a period of p instead of . Then, the new function can be introduced by: for all values of j, which it is, implies that must be real and then: ISSN: 2180-1053 Vol. 2 No. 1 January-June 2010 Image Classification of Temperature Distribution Using Fourier Series Strategy 15 2.0 FOURIER SERIES STRATEGY Fourier series is a one method to analyze the periodic phenomenon and they occur quite frequently in engineering and elsewhere such as in rotating of machines, alternating electric currents or the motions of planets. Fourier series is also called as a Trigonometric series and it represent in periodic functions. The function on trigonometric can be defined from , and has a period of of if for all values of x. According to the definition of the periodic, most practical situations such as a function can be expressed as a complex Fourier series like (Kreysig, 2006), (Black, 2008): The number is called as complex coefficients periodic functions. It can be compute by the integration as: This Fourier series also can be written as sine and cosine function. The new equation of this Fourier series represents as a: By the denoting the equation: Yields: This series is called a Fourier sine-cosine expansion. For this case, for all values of j, which it is, implies that must be real and then: Suppose that, Fourier series expansion for a more general function of and having a period of p instead of . Then, the new function can be introduced by: Suppose that, Fourier series expansion for a more general function of and having a period of p instead of . Then, the new function can be introduced by: This has a period of . This function of can be rewrite to a new equation and representing as: Whereas: Therefore the equation can be express into: Sometimes, there occur functions that can be expanding as a series of a sine term only or as a series of cosine terms only. In a case, if the function is originally defined for Therefore, it can be making as a This is a series where it involves only a sine terms. Similarly that, if This term consists only cosine term and finally, the equation can be represented as: This has a period of . This function of can be rewrite to a new equation and representing as: This has a period of . This function of can be rewrite to a new equation and representing as: Whereas: Therefore the equation can be express into: Sometimes, there occur functions that can be expanding as a series of a sine term only or as a series of cosine terms only. In a case, if the function is originally defined for Therefore, it can be making as a This is a series where it involves only a sine terms. Similarly that, if This term consists only cosine term and finally, the equation can be represented as: Where as: This has a period of . This function of can be rewrite to a new equation and representing as: Whereas: Therefore the equation can be express into: Sometimes, there occur functions that can be expanding as a series of a sine term only or as a series of cosine terms only. In a case, if the function is originally defined for Therefore, it can be making as a This is a series where it involves only a sine terms. Similarly that, if This term consists only cosine term and finally, the equation can be represented as: Therefore the equation can be express into: This has a period of . This function of can be rewrite to a new equation and representing as: Whereas: Therefore the equation can be express into: Sometimes, there occur functions that can be expanding as a series of a sine term only or as a series of cosine terms only. In a case, if the function is originally defined for Therefore, it can be making as a This is a series where it involves only a sine terms. Similarly that, if This term consists only cosine term and finally, the equation can be represented as: Sometimes, there occur functions that can be expanding as a series of a sine term only or as a series of cosine terms only. In a case, if the function is originally defined for This has a period of . This function of can be rewrite to a new equation and representing as: Whereas: Therefore the equation can be express into: Sometimes, there occur functions that can be expanding as a series of a sine term only or as a series of cosine terms only. In a case, if the function is originally defined for Therefore, it can be making as a This is a series where it involves only a sine terms. Similarly that, if This term consists only cosine term and finally, the equation can be represented as: Therefore, it can be making as a This has a period of . This function of can be rewrite to a new equation and representing as: Whereas: Therefore the equation can be express into: Sometimes, there occur functions that can be expanding as a series of a sine term only or as a series of cosine terms only. In a case, if the function is originally defined for Therefore, it can be making as a This is a series where it involves only a sine terms. Similarly that, if This term consists only cosine term and finally, the equation can be represented as: This is a series where it involves only a sine terms. Similarly that, if This has a period of . This function of can be rewrite to a new equation and representing as: Whereas: Therefore the equation can be express into: Sometimes, there occur functions that can be expanding as a series of a sine term only or as a series of cosine terms only. In a case, if the function is originally defined for Therefore, it can be making as a This is a series where it involves only a sine terms. Similarly that, if This term consists only cosine term and finally, the equation can be represented as: ISSN: 2180-1053 Vol. 2 No. 1 January-June 2010 Journal of Mechanical Engineering and Technology 16 This term consists only cosine term and finally, the equation can be represented as: This has a period of . This function of can be rewrite to a new equation and representing as: Whereas: Therefore the equation can be express into: Sometimes, there occur functions that can be expanding as a series of a sine term only or as a series of cosine terms only. In a case, if the function is originally defined for Therefore, it can be making as a This is a series where it involves only a sine terms. Similarly that, if This term consists only cosine term and finally, the equation can be represented as: Whereas, this equation can be modifying as: Whereas, this equation can be modifying as: Fourier series is a function of approximation using a finite number of terms and then, the resulting function may oscillate in regions where the actual function is discontinues or in other hand it is called as changes rapidly. This undesirable behaviour can be reduced by using a smoothing procedure described by Lanezos where it use this Fourier series and close it related to a function of and it is defined by a local averaging process according to Equation 16 below. The averaging interval of should be a small fraction of the period of . Then, rewrite the equation of with . The functions of and are identical as . Hence, also match exactly at any point of x, where varies linearly between Importantly, this agreed closely with for a small value of but at the same time in a Fourier series which converges more rapidly than the series for . Last but not least, it can be defined as: Where and for . Then, evidently this Fourier series of the coefficients of are easily obtained from the function of . When this series for converges slowly, using the same number of the terms in the series for often gives an approximation preferable to that provided by the series of . Finally this process is called as smoothing. Fourier series is a function of approximation using a finite number of terms and then, the resulting function may oscillate in regions where the actual function is discontinues or in other hand it is called as changes rapidly. This undesirable behaviour can be reduced by using a smoothing procedure described by Lanezos where it use this Fourier series and close it related to a function of and it is defined by a local averaging process according to Equation 16 below. Whereas, this equation can be modifying as: Fourier series is a function of approximation using a finite number of terms and then, the resulting function may oscillate in regions where the actual function is discontinues or in other hand it is called as changes rapidly. This undesirable behaviour can be reduced by using a smoothing procedure described by Lanezos where it use this Fourier series and close it related to a function of and it is defined by a local averaging process according to Equation 16 below. The averaging interval of should be a small fraction of the period of . Then, rewrite the equation of with . The functions of and are identical as . Hence, also match exactly at any point of x, where varies linearly between Importantly, this agreed closely with for a small value of but at the same time in a Fourier series which converges more rapidly than the series for . Last but not least, it can be defined as: Where and for . Then, evidently this Fourier series of the coefficients of are easily obtained from the function of . When this series for converges slowly, using the same number of the terms in the series for often gives an approximation preferable to that provided by the series of . Finally this process is called as smoothing. The averaging interval of should be a small fraction of the period of . Then, rewrite the equation of with . The functions of and are identical as . Hence, also match exactly at any point of x, where varies linearly between Whereas, this equation can be modifying as: Fourier series is a function of approximation using a finite number of terms and then, the resulting function may oscillate in regions where the actual function is discontinues or in other hand it is called as changes rapidly. This undesirable behaviour can be reduced by using a smoothing procedure described by Lanezos where it use this Fourier series and close it related to a function of and it is defined by a local averaging process according to Equation 16 below. The averaging interval of should be a small fraction of the period of . Then, rewrite the equation of with . The functions of and are identical as . Hence, also match exactly at any point of x, where varies linearly between Importantly, this agreed closely with for a small value of but at the same time in a Fourier series which converges more rapidly than the series for . Last but not least, it can be defined as: Where and for . Then, evidently this Fourier series of the coefficients of are easily obtained from the function of . When this series for converges slowly, using the same number of the terms in the series for often gives an approximation preferable to that provided by the series of . Finally this process is called as smoothing. Importantly, this agreed closely with for a small value of but at the same time in a Fourier series which converges more rapidly than the series for . Last but not least, it can be defined as: Whereas, this equation can be modifying as: Fourier series is a function of approximation using a finite number of terms and then, the resulting function may oscillate in regions where the actual function is discontinues or in other hand it is called as changes rapidly. This undesirable behaviour can be reduced by using a smoothing procedure described by Lanezos where it use this Fourier series and close it related to a function of and it is defined by a local averaging process according to Equation 16 below. The averaging interval of should be a small fraction of the period of . Then, rewrite the equation of with . The functions of and are identical as . Hence, also match exactly at any point of x, where varies linearly between Importantly, this agreed closely with for a small value of but at the same time in a Fourier series which converges more rapidly than the series for . Last but not least, it can be defined as: Where and for . Then, evidently this Fourier series of the coefficients of are easily obtained from the function of . When this series for converges slowly, using the same number of the terms in the series for often gives an approximation preferable to that provided by the series of . Finally this process is called as smoothing. ISSN: 2180-1053 Vol. 2 No. 1 January-June 2010 Image Classification of Temperature Distribution Using Fourier Series Strategy 17 Where Whereas, this equation can be modifying as: Fourier series is a function of approximation using a finite number of terms and then, the resulting function may oscillate in regions where the actual function is discontinues or in other hand it is called as changes rapidly. This undesirable behaviour can be reduced by using a smoothing procedure described by Lanezos where it use this Fourier series and close it related to a function of and it is defined by a local averaging process according to Equation 16 below. The averaging interval of should be a small fraction of the period of . Then, rewrite the equation of with . The functions of and are identical as . Hence, also match exactly at any point of x, where varies linearly between Importantly, this agreed closely with for a small value of but at the same time in a Fourier series which converges more rapidly than the series for . Last but not least, it can be defined as: Where and for . Then, evidently this Fourier series of the coefficients of are easily obtained from the function of . When this series for converges slowly, using the same number of the terms in the series for often gives an approximation preferable to that provided by the series of . Finally this process is called as smoothing. and Whereas, this equation can be modifying as: Fourier series is a function of approximation using a finite number of terms and then, the resulting function may oscillate in regions where the actual function is discontinues or in other hand it is called as changes rapidly. This undesirable behaviour can be reduced by using a smoothing procedure described by Lanezos where it use this Fourier series and close it related to a function of and it is defined by a local averaging process according to Equation 16 below. The averaging interval of should be a small fraction of the period of . Then, rewrite the equation of with . The functions of and are identical as . Hence, also match exactly at any point of x, where varies linearly between Importantly, this agreed closely with for a small value of but at the same time in a Fourier series which converges more rapidly than the series for . Last but not least, it can be defined as: Where and for . Then, evidently this Fourier series of the coefficients of are easily obtained from the function of . When this series for converges slowly, using the same number of the terms in the series for often gives an approximation preferable to that provided by the series of . Finally this process is called as smoothing. Then, evidently this Fourier series of the coefficients of are easily obtained from the function of . When this series for converges slowly, using the same number of the terms in the series for often gives an approximation preferable to that provided by the series of . Finally this process is called as smoothing. 3.0 fourIer serIes analysIs of tHIn sQuare metal plate T 0 0 0 y = π x = 0 y = 0 x = π FIGURE 1 Plate A thin square metal plate has three sides that are held at temperature 0. The other side (the top) is fixed at a temperature above 0. Using the boundary conditions: 3.0 FOURIER SERIES ANALYSIS OF THIN SQUARE METAL PLATE FIGURE 1 Plate A thin square metal plate has three sides that are held at temperature 0. The other side (the top) is fixed at a temperature above 0. Using the boundary conditions: According to the Laplace Equation, it can be derived as a: Let: Since, Where, T 0 0 0 y = π x = 0 y = 0 x = π According to the Laplace Equation, it can be derived as a: 3.0 FOURIER SERIES ANALYSIS OF THIN SQUARE METAL PLATE FIGURE 1 Plate A thin square metal plate has three sides that are held at temperature 0. The other side (the top) is fixed at a temperature above 0. Using the boundary conditions: According to the Laplace Equation, it can be derived as a: Let: Since, Where, T 0 0 0 y = π x = 0 y = 0 x = π ISSN: 2180-1053 Vol. 2 No. 1 January-June 2010 Journal of Mechanical Engineering and Technology 18 Let: 3.0 FOURIER SERIES ANALYSIS OF THIN SQUARE METAL PLATE FIGURE 1 Plate A thin square metal plate has three sides that are held at temperature 0. The other side (the top) is fixed at a temperature above 0. Using the boundary conditions: According to the Laplace Equation, it can be derived as a: Let: Since, Where, T 0 0 0 y = π x = 0 y = 0 x = π Since, Where, From Equation 20, it can be rewritten as: From Equation 20, it can be rewritten as: Re-arrange the equation and substitute Equation 21 and 22 into . The new equation can be written as: From Equation 23, it needs to be divided with FG. Therefore, the equation can be expressed as: Based on Equation 24, equating the equation with where it is a constant value. Re-written of Equation 24 is: Hence, And So, From Equation 20, it can be rewritten as: Re-arrange the equation and substitute Equation 21 and 22 into . The new equation can be written as: From Equation 23, it needs to be divided with FG. Therefore, the equation can be expressed as: Based on Equation 24, equating the equation with where it is a constant value. Re-written of Equation 24 is: Hence, And So, Re-arrange the equation and substitute Equation 21 and 22 into From Equation 20, it can be rewritten as: Re-arrange the equation and substitute Equation 21 and 22 into . The new equation can be written as: From Equation 23, it needs to be divided with FG. Therefore, the equation can be expressed as: Based on Equation 24, equating the equation with where it is a constant value. Re-written of Equation 24 is: Hence, And So, The new equation can be written as: From Equation 20, it can be rewritten as: Re-arrange the equation and substitute Equation 21 and 22 into . The new equation can be written as: From Equation 23, it needs to be divided with FG. Therefore, the equation can be expressed as: Based on Equation 24, equating the equation with where it is a constant value. Re-written of Equation 24 is: Hence, And So, From Equation 20, it can be rewritten as: Re-arrange the equation and substitute Equation 21 and 22 into . The new equation can be written as: From Equation 23, it needs to be divided with FG. Therefore, the equation can be expressed as: Based on Equation 24, equating the equation with where it is a constant value. Re-written of Equation 24 is: Hence, And So, From Equation 23, it needs to be divided with FG. Therefore, the equation can be expressed as: From Equation 20, it can be rewritten as: Re-arrange the equation and substitute Equation 21 and 22 into . The new equation can be written as: From Equation 23, it needs to be divided with FG. Therefore, the equation can be expressed as: Based on Equation 24, equating the equation with where it is a constant value. Re-written of Equation 24 is: Hence, And So, Based on Equation 24, equating the equation with where it is a constant value. Re-written of Equation 24 is: From Equation 20, it can be rewritten as: Re-arrange the equation and substitute Equation 21 and 22 into . The new equation can be written as: From Equation 23, it needs to be divided with FG. Therefore, the equation can be expressed as: Based on Equation 24, equating the equation with where it is a constant value. Re-written of Equation 24 is: Hence, And So, ISSN: 2180-1053 Vol. 2 No. 1 January-June 2010 Image Classification of Temperature Distribution Using Fourier Series Strategy 19 Hence, From Equation 20, it can be rewritten as: Re-arrange the equation and substitute Equation 21 and 22 into . The new equation can be written as: From Equation 23, it needs to be divided with FG. Therefore, the equation can be expressed as: Based on Equation 24, equating the equation with where it is a constant value. Re-written of Equation 24 is: Hence, And So, And So, From Equation 20, it can be rewritten as: Re-arrange the equation and substitute Equation 21 and 22 into . The new equation can be written as: From Equation 23, it needs to be divided with FG. Therefore, the equation can be expressed as: Based on Equation 24, equating the equation with where it is a constant value. Re-written of Equation 24 is: Hence, And So, The left and the right side of the boundary conditions can be implied as: It can give as a: Hence that, The Ordinary Differential Equations (ODEs) for G with can represent as a: Then, From Equation 28, differentiate respect to y by putting boundary condition Obtained A = B. Therefore from Equation 28: From Equation 29, using Euler’s formula in trigonometry, the equation can be expressed as: Multiply both F and G, represent the equation as a: The boundary condition of then is applied at the top side of the thin plate which subsequently the Equation 31 can be rewritten again as: The left and the right side of the boundary conditions can be implied as: It can give as a: The left and the right side of the boundary conditions can be implied as: It can give as a: Hence that, The Ordinary Differential Equations (ODEs) for G with can represent as a: Then, From Equation 28, differentiate respect to y by putting boundary condition Obtained A = B. Therefore from Equation 28: From Equation 29, using Euler’s formula in trigonometry, the equation can be expressed as: Multiply both F and G, represent the equation as a: The boundary condition of then is applied at the top side of the thin plate which subsequently the Equation 31 can be rewritten again as: Hence that, The left and the right side of the boundary conditions can be implied as: It can give as a: Hence that, The Ordinary Differential Equations (ODEs) for G with can represent as a: Then, From Equation 28, differentiate respect to y by putting boundary condition Obtained A = B. Therefore from Equation 28: From Equation 29, using Euler’s formula in trigonometry, the equation can be expressed as: Multiply both F and G, represent the equation as a: The boundary condition of then is applied at the top side of the thin plate which subsequently the Equation 31 can be rewritten again as: The Ordinary Differential Equations (ODEs) for G with can represent as a: The left and the right side of the boundary conditions can be implied as: It can give as a: Hence that, The Ordinary Differential Equations (ODEs) for G with can represent as a: Then, From Equation 28, differentiate respect to y by putting boundary condition Obtained A = B. Therefore from Equation 28: From Equation 29, using Euler’s formula in trigonometry, the equation can be expressed as: Multiply both F and G, represent the equation as a: The boundary condition of then is applied at the top side of the thin plate which subsequently the Equation 31 can be rewritten again as: ISSN: 2180-1053 Vol. 2 No. 1 January-June 2010 Journal of Mechanical Engineering and Technology 20 Then, The left and the right side of the boundary conditions can be implied as: It can give as a: Hence that, The Ordinary Differential Equations (ODEs) for G with can represent as a: Then, From Equation 28, differentiate respect to y by putting boundary condition Obtained A = B. Therefore from Equation 28: From Equation 29, using Euler’s formula in trigonometry, the equation can be expressed as: Multiply both F and G, represent the equation as a: The boundary condition of then is applied at the top side of the thin plate which subsequently the Equation 31 can be rewritten again as: From Equation 28, differentiate respect to y by putting boundary condition The left and the right side of the boundary conditions can be implied as: It can give as a: Hence that, The Ordinary Differential Equations (ODEs) for G with can represent as a: Then, From Equation 28, differentiate respect to y by putting boundary condition Obtained A = B. Therefore from Equation 28: From Equation 29, using Euler’s formula in trigonometry, the equation can be expressed as: Multiply both F and G, represent the equation as a: The boundary condition of then is applied at the top side of the thin plate which subsequently the Equation 31 can be rewritten again as: Obtained A = B. Therefore from Equation 28: The left and the right side of the boundary conditions can be implied as: It can give as a: Hence that, The Ordinary Differential Equations (ODEs) for G with can represent as a: Then, From Equation 28, differentiate respect to y by putting boundary condition Obtained A = B. Therefore from Equation 28: From Equation 29, using Euler’s formula in trigonometry, the equation can be expressed as: Multiply both F and G, represent the equation as a: The boundary condition of then is applied at the top side of the thin plate which subsequently the Equation 31 can be rewritten again as: From Equation 29, using Euler’s formula in trigonometry, the equation can be expressed as: The left and the right side of the boundary conditions can be implied as: It can give as a: Hence that, The Ordinary Differential Equations (ODEs) for G with can represent as a: Then, From Equation 28, differentiate respect to y by putting boundary condition Obtained A = B. Therefore from Equation 28: From Equation 29, using Euler’s formula in trigonometry, the equation can be expressed as: Multiply both F and G, represent the equation as a: The boundary condition of then is applied at the top side of the thin plate which subsequently the Equation 31 can be rewritten again as: Multiply both F and G, represent the equation as a: The left and the right side of the boundary conditions can be implied as: It can give as a: Hence that, The Ordinary Differential Equations (ODEs) for G with can represent as a: Then, From Equation 28, differentiate respect to y by putting boundary condition Obtained A = B. Therefore from Equation 28: From Equation 29, using Euler’s formula in trigonometry, the equation can be expressed as: Multiply both F and G, represent the equation as a: The boundary condition of then is applied at the top side of the thin plate which subsequently the Equation 31 can be rewritten again as: The boundary condition of then is applied at the top side of the thin plate which subsequently the Equation 31 can be rewritten again as: The final equation can represent as a: Then, If n is even number, n = 2, 4, 6, and 8… Equation 36 will become as: If n is odd number, n = 1, 3, 5, 7 … Therefore, From Equation 37 and above, the general equation of the Fourier series of this problem can be representing as a: The final equation can represent as a: Then, If n is even number, n = 2, 4, 6, and 8… Equation 36 will become as: If n is odd number, n = 1, 3, 5, 7 … Therefore, From Equation 37 and above, the general equation of the Fourier series of this problem can be representing as a: The final equation can represent as a: The final equation can represent as a: Then, If n is even number, n = 2, 4, 6, and 8… Equation 36 will become as: If n is odd number, n = 1, 3, 5, 7 … Therefore, From Equation 37 and above, the general equation of the Fourier series of this problem can be representing as a: The final equation can represent as a: Then, If n is even number, n = 2, 4, 6, and 8… Equation 36 will become as: If n is odd number, n = 1, 3, 5, 7 … Therefore, From Equation 37 and above, the general equation of the Fourier series of this problem can be representing as a: ISSN: 2180-1053 Vol. 2 No. 1 January-June 2010 Image Classification of Temperature Distribution Using Fourier Series Strategy 21 Then, The final equation can represent as a: Then, If n is even number, n = 2, 4, 6, and 8… Equation 36 will become as: If n is odd number, n = 1, 3, 5, 7 … Therefore, From Equation 37 and above, the general equation of the Fourier series of this problem can be representing as a: If n is even number, n = 2, 4, 6, and 8… Equation 36 will become as: The final equation can represent as a: Then, If n is even number, n = 2, 4, 6, and 8… Equation 36 will become as: If n is odd number, n = 1, 3, 5, 7 … Therefore, From Equation 37 and above, the general equation of the Fourier series of this problem can be representing as a: If n is odd number, n = 1, 3, 5, 7 … The final equation can represent as a: Then, If n is even number, n = 2, 4, 6, and 8… Equation 36 will become as: If n is odd number, n = 1, 3, 5, 7 … Therefore, From Equation 37 and above, the general equation of the Fourier series of this problem can be representing as a: Therefore, The final equation can represent as a: Then, If n is even number, n = 2, 4, 6, and 8… Equation 36 will become as: If n is odd number, n = 1, 3, 5, 7 … Therefore, From Equation 37 and above, the general equation of the Fourier series of this problem can be representing as a: The final equation can represent as a: Then, If n is even number, n = 2, 4, 6, and 8… Equation 36 will become as: If n is odd number, n = 1, 3, 5, 7 … Therefore, From Equation 37 and above, the general equation of the Fourier series of this problem can be representing as a: From Equation 37 and above, the general equation of the Fourier series of this problem can be representing as a: The final equation can represent as a: Then, If n is even number, n = 2, 4, 6, and 8… Equation 36 will become as: If n is odd number, n = 1, 3, 5, 7 … Therefore, From Equation 37 and above, the general equation of the Fourier series of this problem can be representing as a: When n = 1 ISSN: 2180-1053 Vol. 2 No. 1 January-June 2010 Journal of Mechanical Engineering and Technology 22 4.0 result anD DIsCussIon Un(x , y )=-2T/pi * s um [ (c os nx -1)s in nx s inh ny / n s inh npi ] x y 0 0. 5 1 1. 5 2 2. 5 3 0 0. 5 1 1. 5 2 2. 5 3 0 10 20 30 40 50 60 70 80 90 100 110 FIGURE 2 Temperature contour of thin square metal plate x y 0 0. 5 1 1. 5 2 2. 5 3 0 0. 5 1 1. 5 2 2. 5 3 FIGURE 3 Isotherms line of thin square metal plate 0 0. 5 1 1. 5 2 2. 5 3 0 0. 5 1 1. 5 2 2. 5 3 x y 20 40 60 80 100 120 FIGURE 4 Two dimensional of thin square metal plate ISSN: 2180-1053 Vol. 2 No. 1 January-June 2010 Image Classification of Temperature Distribution Using Fourier Series Strategy 23 0 1 2 3 4 0 1 2 3 4 0 0. 2 0. 4 0. 6 0. 8 1 xy u (x ,y ) 0. 1 0. 2 0. 3 0. 4 0. 5 0. 6 0. 7 0. 8 0. 9 FIGURE 5 Three dimensional of thin square metal plate Figure 2 shows the temperature contour of thin square metal plate. It can be seen that heat is transfer from high temperature to low temperature. The direction of heat transfer is due to temperature setting at the boundary condition. Left and right edges are set as cold (T=0) and the bottom edge set as an adiabatic boundary condition and the top edge is set at temperature T. Isotherm lines was plotted in Figure 3, it shows isotherm move out from the bottom edge. This is due the adiabatic boundary condition. At the left and right edges of thin plate, the isotherm lines keep parallel with these edges. This occurs due to left and right edges of thin plate was set as a cold (T=0). Figure 4 and Figure 5 show the two and three dimensional of temperature distribution of thin square metal plate. Figure 5 clearly shows the steady state heat transfer conditions. At steady state condition, heat transfer from the top edge of thin square metal plate is equal to heat transfer out from bottom edge of thin square metal plate. 5.0 ConClusIon Fourier series analysis is also known as a trigonometric series analysis. This series has a potential to solve the analytical solution on temperature distribution of plate. Temperature distribution can be distributed independently according to the adiabatic phenomenon. This phenomenon is based on the time domain. ISSN: 2180-1053 Vol. 2 No. 1 January-June 2010 Journal of Mechanical Engineering and Technology 24 6.0 aCKnoWleDgement The author would like to express appreciation and gratitude to Faculty of Mechanical Engineering, Universiti Teknikal Malaysia Melaka and Universiti Teknologi Malaysia for the technical supports. 7.0 referenCes Erwin Kreysig. 2006. Advanced Engineering Mathematics. 9th Edition. Wiley International Edition. Howard B. Wilson, Louis H. Turcotte and David Halpen. 2003. Advanced Mathematics and Mechanics and Application Using MATLAB. 3rd Edition. Chapman and Hall. Maksimovich, V. N and Tsybul’’skii, O. A. 2004. Application of fourier- series methods and integral equations for solving nonstationary nonaxisymmetric heat conduction problems for bodies of revolution Journal of Engineering Physics and Thermophysics Volume 68, Number 6 / November, 1995 pp828-834 Maria T. Ibanez and H. Power, 2000. An efficient direct BEM numerical scheme for heat transfer problems using Fourier series, International Journal of Numerical Methods for Heat & Fluid Flow Vol. 10/7 ISSN 0961-5539 pp 687 - 720 S. Bochner, 1935. Summation of Derived Fourier Series. An application to Fourier expansions on compact Lie groups. Annals of Mathematics. Vol 37, No. 2 Taddeus H. Black. 2008. Derivation of Applied Mathematics. Revised. Debian Project.