Abstract: In order to improve the fast and accurate evaluation of the operation status of the switchgear, a switchgear fault identification method based on the optimal feature quantity of multiple types of data is proposed. Based on the real-time monitoring of various types of switchgear electrical quantities and non-electrical parameters, the principle of minimum redundancy maximum relevance（MRMR） is adopted to process the collected switchgear operating parameters to obtain feature samples, and optimize them to obtain the optimal feature subset. The adopted Mahalanobis distance method compares the real-time monitored operating status feature quantity with the standard setting sample to determine the fault state of the switchgear. Practical tests and analysis of calculation examples show that the proposed method can effectively improve the accuracy and efficiency of fault identification.