A Simple and Efficient Current-Based Method for Interturn Fault Detection in BLDC Motors

Fault diagnosis of brushless direct current (BLDC) motors has recently gained much attention. Interturn faults in BLDC motor distort three-phase currents waveforms, leading to an asymmetrical condition. In this article, we introduce a simple and efficient method to detect interturn faults based on one modal current and four different simple indices. The modal current is derived by proper linear mixing of measured three-phase currents. Following the initial processing of the modal current, three main indices, including moving mean, variance, and signal energy, are obtained in parallel. Also, an auxiliary correlation-based index is suggested to enhance the method for discrimination of faulty conditions from healthy ones. The fault detection is made by passing at least two main indices (out of three indices), and also an auxiliary index from a predefined threshold. The proposed technique is evaluated under different loads, speeds, and fault severities in two different datasets: data from a simulated motor in Maxwell finite element package, and a real four-pole motor. Moreover, the method is compared with other methods from different aspects. The results confirm a high accuracy and quick fault detection in the proposed approach.