Abstract:

The state recognition of AC contactor is an important prerequisite to ensure its normal operation.In view of the characteristics of multivariate,multi-attribute interaction and dynamic change of AC contactor operation state,an AC contactor operation state recognition method based on Grey Wolf optimizer support vector machine (GWO-SVM) is proposed.The time domain and frequency domain features are extracted from the vibration signal of the contactor contact opening and closing stage,and the Pearson correlation coefficient is used to select the parameters to obtain the optimal feature subset.Finally,the contactor operation state is identified by GWO-SVM method.By comparing other identification algorithms,it shows that the proposed method is better in the recognition accuracy of the contactor operation state.

Key words: AC contactor, feature selection, Gray Wolf algorithm, support vector machine(SVM)