Application of K-Nearest Neighbor Machine Learning Algorithm in High Voltage Circuit Breaker Monitoring System by Analyzing Spring Mechanism Motor Current

Machine learning has been applied across various scientific fields and switching apparatus monitoring is no exception. Monitoring system is a crucial component of switching apparatus maintenance, as it ensures system reliability while minimizing both economic and time losses. This paper demonstrates how to interpret faults in the operation of a high-voltage circuit breaker spring motor mechanism. Furthermore, it describes the implementation of the K-Nearest Neighbor machine learning algorithm for fault detection by observing DC motor currents.