Inverter statistics for online detection of stator asymmetries in inverter-fed induction motors

Abstract

A simulation model of an induction machine that enables the analysis of the influence of stator fault conditions on the machine control of inverter-fed drives is presented. Based on this model, the influence of the breakdown of the stator windings insulation on the behavior of the machine and especially on the current control scheme is shown. A new online method to detect such asymmetries caused, for example, by an interturn insulation failure in the stator windings is proposed and investigated. This new method utilizes the influence of stator asymmetries on the inverter current control scheme. By evaluating the statistical distribution of the different inverter switching states and switching times, asymmetries in the stator can be detected and isolated. The measurements required to implement this method are already available in modern inverter fed drives as they are used to realize the current control loop. Thus, no additional sensors are necessary. The practical realization of the fault detection algorithm is demonstrated in combination with a predictive single step current controller. Measurements performed on a drive test stand verify the applicability of the proposed online method to detect and isolate stator faults.