Construction of Power Equipment Running Status Monitoring System Based on Infrared Temperature Measurement Technology and Big Data Algorithm

At present, with the rapid growth of power demand every year and the commercial operation of power enterprises, the health status and maintenance cost of power transmission and transformation equipment directly affect the reliability of equipment operation, enterprise benefits and market competitiveness. In this paper, the construction of power equipment running status monitoring system based on infrared temperature measurement technology and big data algorithm is launched. In the design scheme of this system, the infrared thermal imager is used as the acquisition core, the high-performance industrial computer is used as the processing core, and the network communication technology based on TCP/IP protocol is used to form a powerful and easy-to-operate power transformer running status monitoring system. A selective oversampling mechanism and an integrated classifier updating algorithm with central nodes are designed to improve the accuracy of the model in identifying small-class samples. The research results show that the mining error rate of this method has dropped to 8% after 800s learning. The running time of optimized feature extraction is only about 32% of that of standard platform. The data stream is classified by mining local nodes and central nodes.