Research on the Preprocessing Method of Switchgear Operation Data Based on Clustering Algorithm*

Considering the high requirements for the safety of switchgear equipment and the extremely large amount of data in the process of equipment condition monitoring, a preprocessing method based on K-means clustering of switchgear equipment operation data is proposed. The method firstly selects evaluation parameters from multiple fault problem aspects to ensure the reliability of condition monitoring; then it considers the characteristics of different data volumes, quantifies the non-data volume information, and forms a unified data format; finally, it concentrates the massive operation data through K-means clustering algorithm. Using this method to analyze the switchgear operation data of a city in North China, an accuracy index is introduced to evaluate the performance of the algorithm in the clustering task, and the experimental results show that the method can realize the normalization and effective compression of switchgear equipment operation data.