Electric Fault Diagnosis and Detection in an Induction Machine Using RMS Based Method

Abstract

Nowadays, induction machines are widely used in industry thankful to their advantages comparing to other technologies. Indeed, there is a big demand because of their reliability, robustness and cost. The objective of this paper is to deal with diagnosis, detection and isolation of faults in a three-phase induction machine. Among the faults, Inter-turn short-circuit fault (ITSC), current sensors fault and single-phase open circuit fault are selected to deal with. However, a new method is developed for fault detection using residual errors generated by the root mean square (RMS) of phase currents. This approach is based on an asymmetric nonlinear model of Induction Machine where the winding fault of the three axes frame state space is taken into account. In addition, current sensor redundancy and sensor fault detection and isolation (FDI) are adopted to ensure safety operation of induction machine drive. Finally, a validation is carried out by simulation in healthy and faulty operation modes to show the benefit of the proposed method to detect and to locate with, a high reliability, the three types of faults.