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An intellegent vehicle oriented EMC reverse diagnostic model based on SVM

The rapid development of intelligent vehicles brings new challenges to vehicle EMC design, which is benefited from test data-oriented troubleshooting. With the increase in electronic complexity, vehicle on-board system designers should confront with more and more EMC failure possibilities and are in need of effective EMC failure diagnosis approach. However, EMC fault diagnosis is difficult due to the distinguishing features of EMC test dataset, such as small sample, nonlinear, high dimensions, etc. Hence, in this paper, EMC reverse diagnostic model is proposed. Firstly, EMC feature extraction method is designed. Then SVM model is designed to realize EMC faults classification. Corresponding application effect is displayed. Experiment results show that proposed method could match the demand of EMC fault diagnosis for intelligent vehicles.