Winding fault detection based on current information of induction motors

As an information carrier, current signal directly reflects the electromechanical coupling between the stator and rotor of an induction motor. In this study, a detection method of winding fault based on current information is proposed to identify fault and realize feature decoupling for an induction motor. Unlike most current analysis methods, this method combines the electromagnetic field distribution with the feature frequency of the current signal to achieve the detection of the stator winding fault. With mathematical models, the phase, amplitude, and frequency of the three-phase current are mapped into a spatial coordinate system, which can help to identify the faults of the induction motor by a balance structure. To further identify the fault features, the projections of the coupled magnetic fields are combined with the feature frequencies, which can be used to extract accurately the electromechanical information on the stator and rotor. And the proposed methods are verified by a test bench of motor fault. The results show that the proposed methods can effectively detect a stator winding fault of the frequency conversion motor using the distributions of the magnetic motive forces and the feature frequencies of the current signals. The method proposed in this study provides a new tool for the fault detection and condition monitoring of induction motors.