Research On Partial Discharge Detection Technology Of Power Cable

With the development of modern industry and the improvement of urbanization level,power cable as an important tool for transmitting electrical energy has been paid more and more attention,and the reliability of its operation directly affects the normal operation of the power system.Therefore,it is necessary to monitor the fault of the high-voltage power cable.The fault of the power cable is closely related to its insulation condition.The main insulation has defects and there is a partial discharge phenomenon.The change of the partial discharge quantity also indicates that the cable insulation has defects that may endanger the safe operation of the cable.Therefore,accurately measuring the partial discharge of the cable is the most intuitive and ideal method to judge the insulation quality of the cable.The partial discharge monitoring analysis is of great significance for the judgment of the power cable fault.This paper first introduces the basic theory of partial discharge of power cable,including the concept of partial discharge and its basic types,analyzes the generation mechanism of partial discharge ultrasonic signal of power cable,and summarizes its spectral characteristics.Then,this paper studies the first important part of power cable partial discharge monitoring technology,namely the power cable partial discharge detection denoising method.The wavelet packet analysis is used to suppress the white noise in the online monitoring of partial discharge of power cable,and the threshold function is proposed.According to the characteristics of the partial discharge signal of the cable,an improved threshold function is proposed.Compared with the traditional hard threshold function and soft threshold function,the simulation results show that the improved algorithm denoising effect is better than the traditional threshold function processing method.Finally,the second important part of the cable PD monitoring technology,namely,the research of the power cable PD detection pattern recognition method.Through wavelet packet decomposition of PD signal sample waveform,the corresponding wavelet packet coefficients are obtained and the energy proportion of each frequency band is calculated to construct the energy eigenvector.BP neural network algorithm is used to identify the frequency band energy proportion of wavelet packet coefficients and the energy characteristics extracted from the inherent mode,so as to realize the classification of partial discharge signals caused by different insulation defects.