Intelligent Detection Algorithm of Medium and Low Voltage Switch Performance Based on the Improved K-means Clustering

Abstract

The performance of medium and low voltage switches will directly affect the reliability of medium and low voltage distribution networks. The medium and low voltage switch algorithm’s failure form is mainly mechanical. In order to realize its intelligent detection, a medium and low voltage switch detection algorithm based on the improved K-means clustering algorithm is proposed. Optimizing the algorithm’s clustering center selection establishes a model of the switch working state under different vibration signals and an intelligent detection algorithm for medium and low voltage switches with intelligent judgment, adaptive adjustment, and remote fault diagnosis. Experiments show that: the detection algorithm of the medium and low voltage switch controller based on the improved K-means algorithm can more accurately identify the fault of the switch algorithm according to the vibration signals, which provides a new idea for the fault identification and monitoring of the medium and low voltage switch.