Skewness Scanning for Diagnosis of a Small Inter-Turn Fault in Quadcopter’s Motor Based on Motor Current Signature Analysis

This paper deals with hall sensor based very small inter-turn short circuit fault assessment of single-phase quadcopter system using current signature analysis of connected brushless DC motors at the transient condition. Firstly, a quadcopter has been modeled with a proportional-differential controller, and roll, pitch, and yaw angles have been adjusted as reference inputs. Secondly, the current signal of each motor has been captured through a hall sensor for monitoring at various conditions. Then, Skewness scanning is performed on multi-resolution analysis based wavelet coefficients obtained from the starting transients. Variation in the asymmetrical distribution of coefficients has been observed at different decomposition levels. Levels that show almost linear variation with the increase of fault are selected for fault detection. An algorithm of Skewness scanning has been proposed for the detection of the number of shorted turns present in the system. Practical validation of the work has been done with data captured by the data acquisition system through the Hall probe; satisfactory diagnosis has been observed in experimentation.