International Journal of Information Engineering and Electronic Business (IJIEEB)
IJIEEB Vol. 2, No. 1, 8 Nov. 2010
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Comparison of Two Methods Basing on Artificial Neural Network and SVM in Fault Diagnosis
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Author(s)
Chunming Li
1,*
Huiling Li
1
Index Terms
Neural network, SVM, fault diagnosis
Abstract
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.
Cite This Paper
Chunming Li, Huiling Li, "Comparison of Two Methods Basing on Artificial Neural Network and SVM in Fault Diagnosis", International Journal of Information Engineering and Electronic Business(IJIEEB), vol.2, no.1, pp.23-29, 2010. DOI:10.5815/ijieeb.2010.01.04
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