Neural network based on-line stator winding turn fault detection for induction motors

A novel on-line neural network based diagnostic scheme, for induction machine stator winding turn fault detection, is presented. The scheme consists of a feed-forward neural network combined with a self-organizing feature map (SOFM) to visually display the operating condition of the machine on a two-dimensional grid. The operating point moves to a specific region on the map as a fault starts developing and can be used to alert the motor protection system to an incipient fault. This is a useful tool for commercial condition monitoring systems. Experimental results are provided, with data obtained from a specially wound test motor, to illustrate the robustness of the proposed turn fault detection scheme. The new method is not sensitive to unbalanced supply voltages or asymmetries in the machine and instrumentation.