Title :
Motor Fault Diagnosis Based on Wavelet Neural Network
Author :
Ying, Xu Li ; Lan, Wang Nan
Author_Institution :
Changsha Univ. of Sci. & Technol., Changsha, China
Abstract :
Motor fault diagnosis is important in industrial and agricultural production. Many methods have been employed to solve this problem. A novel method for motor fault diagnosis is proposed in this paper, which adopts the wavelet neural network and applies improved genetic algorithm to optimize the initial parameters of wavelet neural network. The results of training and testing show that the method is effective and available.
Keywords :
electric machine analysis computing; fault diagnosis; genetic algorithms; induction motors; neural nets; agricultural production; genetic algorithm; industrial production; motor fault diagnosis; wavelet neural network; Art; Automation; Computer networks; Convergence; Fault diagnosis; Feedforward neural networks; Genetic algorithms; Intelligent networks; Neural networks; Production; motor fault diagnosis; neural network; wavelet function;
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
DOI :
10.1109/ICICTA.2009.368
