Interval Evidential Reasoning-based Fault Detection of Electromagnetic Relay

Abstract

Abstract The electromagnetic relay is a key switch control component, and its fault detection under uncertainties is a challenging problem. In this paper, a fault detection method based on interval evidential reasoning (IER) is proposed and applied to detect the relay’s fault. The method can handle fuzzy uncertainty and interval uncertainty in relay test data, and iteratively aggregate evidence by using the IER algorithm. Firstly, the relay super-path time data is transformed into the form of an interval belief distribution by using the fuzzy threshold, which is optimized by using training data. Secondly, historical and current information is aggregated to update interval belief distribution. Finally, the fault detection result can be obtained from interval belief distribution by a rule. The experimental results show that the presented method can improve the detection effect significantly.