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Fault diagnosis of marine diesel engine based on support vector machine

ZHU Zhi-yu, LIU Wei-ting (Dept. of Electronics and Information, Jiangsu University of Science and Technology, Zhenjiang 212003, China)  
The mechanism of support vector machine (SVM) is first introduced in this paper. Then SVM is applied to diagnose faults of marine diesel engine. The method to choose parameters of SVM is studied. The simulation result shows that SVM has good diagnosis effect and strong ability to resist noise. Compared with RBF neural network, SVM has higher diagnosis accuracy on compound fault samples.
【CateGory Index】: U672
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