Abstract
Partial discharge causes mainly the insulation deterioration. It is the significant symptom and manifestation, and is an important factor of the insulation failure for the electrical power equipment. On the basis of analyzing the physical model of partial discharge, this paper used the online monitoring technology of partial discharge that combines the ultra high frequency (UHF) method and the acoustic emission (AE) method, studied the fault pattern recognition method of partial discharge based on the case-based reasoning algorithm, and established the intelligent fault identification system of partial discharge based on the case-based reasoning. The system can accurately and reliably identify the fault mode type, the specific fault location and severity of partial discharge for the electrical power equipment to make the health evaluation and improve the reliability. Through the application of the new materials and new technology, the load loss of the transformer can drop by 15%, the no-load loss can decline by 50% and the fee of electricity loss can down by 32.5%.
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