Faculty of Engineering and Technology, University of Mazandaran, Babolsar, Iran.
Abstract
In the engineering systems, one of the most important measurable parameters is temperature. For measurement of temperature as for sensitivity, accuracy and term of physical required, different sensors as RTD, NTC, PTC, Thermo-couple are exist. One of the most important sensors is NTC that despite the many benefits, less than it used to be. Nonlinearity characteristic and self-heating phenomenon in the NTC are the biggest deterrents in practical applications. In this study, a new structure based on application of artificial neural network (ANN) has been suggested for modeling of the nonlinear and the self-heating phenomenons of NTC. Simulation results based on read generated laboratory data are presented to demonstrate the performance of the proposed structure. Mean square error of 0.0480 and 0.0370 are achieved based on MLP and RBF neural network, respectively.
Ghasemi, J. (2017). Self-heating Phenomenon and Nonlinear Characteristic Modeling of NTC Using Artificial Neural Network for Direct Measurement of Temperature. Journal of Soft Computing and Information Technology, 6(1), 8-15.
MLA
Jamal Ghasemi. "Self-heating Phenomenon and Nonlinear Characteristic Modeling of NTC Using Artificial Neural Network for Direct Measurement of Temperature". Journal of Soft Computing and Information Technology, 6, 1, 2017, 8-15.
HARVARD
Ghasemi, J. (2017). 'Self-heating Phenomenon and Nonlinear Characteristic Modeling of NTC Using Artificial Neural Network for Direct Measurement of Temperature', Journal of Soft Computing and Information Technology, 6(1), pp. 8-15.
VANCOUVER
Ghasemi, J. Self-heating Phenomenon and Nonlinear Characteristic Modeling of NTC Using Artificial Neural Network for Direct Measurement of Temperature. Journal of Soft Computing and Information Technology, 2017; 6(1): 8-15.
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