Evaluating techniques for online detection of generator earth-brush faults
Poor performance of shaft earthing system is caused by a wide range of factors such as the high wear rates of earth-brushes, which reduces shaft earthing contact, the environmental contamination of brushes by seal oil, and carbon dust contamination. This study evaluates online shaft-signal based techniques to classify different earth-brush fault types using shaft current and voltage measurements during operation to monitor the condition of synchronous generator earthing brushes. The effects of shaft earthing brush faults on shaft voltages/currents were successfully determined through physical measurements and experiments using a two-pole, 20 kVA synchronous generator which was designed and built to mimic a full-sized 600 MW turbo generator. Measurements on a two-pole synchronous generator found that the shaft voltages and current characteristics are responsive to the earth-brush faults. The results of an investigation indicated that the shaft voltages and current characteristics have effects on earth-brush fault types. The harmonics of the shaft voltage show a definite trend for the 3rd, 5th, and 9th harmonics which is significant in the diagnosis of an earthing brush fault system. Therefore, it is possible to determine the earth-brush condition from shaft voltage and current measurement given that baseline information is available. The evaluation of shaft-signal based fault detection techniques such as warning criteria, threshold checking and frequency spectral analysis techniques indicated that the frequency spectral analysis technique is the most suitable technique for generator shaft earthing system condition monitoring and exhibits best earthing-brush fault detection capabilities than any of the others. The technique provides a holistic overview of the performance of shaft earthing brushes and does not depend on initially set or benchmark threshold values of the measured quantities.
A dissertation submitted to the School of Electrical and Information Engineering, Faculty of Engineering and Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering, 2022