Development and implementation of an ANN-based fault diagnosis scheme for generator winding protection

In this paper, the development and implementation of a new fault diagnosis scheme for generator winding protection using Artificial Neural Networks (ANN) is introduced. The proposed scheme performs internal fault detection, fault type classifications, and faulted phases identification. This scheme is characterized with higher sensitivity and stability boundaries as compared with the differential relay. Effect of the presence of nonsynchronous frequencies on the scheme performance is examined. Effect of different values of ground resistance on ground fault detection sensitivity is outlined. The scheme hardware is implemented based on a Digital Signal Processing (DSP) board interfaced with a Multi Input/Output (MIO) board. Test results of the proposed scheme corroborate the scheme stability and sensitivity.