Work place: College of Electric Power Inner Mongolia University of Technology, Hohhot, China
E-mail: 499578001@qq.com
Website:
Research Interests: Computational Science and Engineering, Process Control System, Control Theory
Biography
Huiling Li is born in china in July 1985.She is studying in Inner Mongolia University of Technology and her major is control theory and control engineering. She graduated from Xi'an Institute of Post and Telecommunications in 2004. Representative papers are artificial neural network classifier design using genetic algorithm and wavelet transform in fault diagnosis, a fault diagnosis method basing on genetic algorithm and neural network.
DOI: https://doi.org/10.5815/ijieeb.2010.01.04, Pub. Date: 8 Nov. 2010
Two diagnosis methods based on a neural network classifier and SVM are proposed for a pulse width modulation voltage source inverter. They are used to detect and identify the transistor open-circuit fault. BP neural network (BPNN) is capable of recognition. However, it has shortcomings obviously. These are just advantages of SVM, which has ability of global search. As an alternative to ANN, SVM can offer higher detection efficiency and reliability.
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