Research of Electrical Equipment State Identification Based on K-means Clustering Algorithm

Abstract

For the current heavy manual monitoring work and frequent failure of electrical equipment, an online monitoring scheme for equipment state based on current sensor, WIFI communication module and embedded development board is designed. K-means clustering algorithm is used to analyze the current data set collected from different working status of the equipment, and the corresponding characteristic value is obtained. And then the automatic identification of the equipment working status is realized. The experimental results show that this method can quickly recognize the equipment operation status with high accuracy, and working stability. Keywords—electrical equipment; on-line monitoring; current signal; clustering algorithm; state recognition