Title :
Fault diagnosis of power electronic circuits based on neural network and waveform analysis
Author :
Ma, Hao ; Xu, Dehong ; Lee, Yim-Shu
Author_Institution :
Dept. of Electr. Eng., Zhejiang Univ., Hangzhou, China
Abstract :
Based on neural network theory, a new fault diagnosis method for power electronic circuits is presented. By keeping the relations between faults and waveforms in a neural network, the neural network can be trained to detect faults. So automation of fault diagnosis can be realized. In this paper, the fault diagnosis of a three-phase SCR rectifier circuit will be taken as an example to illustrate the new method. Both simulation and experimental results are given
Keywords :
AC-DC power convertors; circuit analysis computing; fault diagnosis; learning (artificial intelligence); neural nets; power engineering computing; rectifying circuits; thyristor convertors; diagnosis automation; neural network; power electronic circuits fault diagnosis; three-phase SCR rectifier circuit; training; waveform analysis; Automation; Circuit faults; Circuit simulation; Electrical fault detection; Fault detection; Fault diagnosis; Neural networks; Power electronics; Rectifiers; Thyristors;
Conference_Titel :
Power Electronics and Drive Systems, 1999. PEDS '99. Proceedings of the IEEE 1999 International Conference on
Print_ISBN :
0-7803-5769-8
DOI :
10.1109/PEDS.1999.794566
