In operation of high voltage circuit breakers

the status feature extraction and analysis are vital for status identification and fault diagnosis. The contact travel curve of a high voltage circuit breaker implies valuable information of operation process

which indicates the mechanical status of the high voltage circuit breaker. However

status of high voltage circuit breakers cannot be identified accurately only by the common parameters

such as time and speed. In this paper

a mechanical status identification method based on optimal feature vector classification is proposed for high voltage circuit breakers. Firstly

the mutual information between each feature and status classifications is calculated and sorted. According to the maximal relevance minimal redundancy

the optimal feature parameters are selected to form the optimal subset of features. Secondly

some support vector machines（SVMs） are built to identify the mechanical status of high voltage circuit breakers based on several features from the subset of optimal features. Then

the optimal feature vector and the optimal SVM classifier are selected according to the evaluation indicator of classification precision. Experimental data show that this method is effective to extract the feature parameters from the contact travel curve

and the accuracy of the SVM classifier with the optimal feature vector is 97%

so it can be used to identify the mechanical status of high voltage circuit breakers.