Neural network system using the multi-layer perceptron technique for the recognition of PD pulse shapes due to cavities and electrical trees

Abstract

A neural network system, utilizing the multi-layer perceptron approach has been applied to distinguish between power cable insulation partial discharge pulse shapes that are characteristic of cavities and electrical trees. The neural network was found to be capable of recognizing the differences in PD pulses produced by single cavity and electrical tree discharge sources. It also could differentiate between the discharge pulse forms emanating from electrical trees of different lengths; likewise, it was able to recognize changes in the shape of the discharge pulses with time due to aging effects. However, as these recognition capabilities relate only to comparisons of single discharge sources on a one-to-one basis, the application of neural networks to PD pulse shape recognition on actual power cables, where a number of different discharge sources may be discharging simultaneously, is quite premature at this time without more detailed exploratory work on complex discharge patterns. >