Study On Mode Recognition Of Partial Discharge In XLPE Cable

With the widely application of XLPE cable and the increasing defaults, the detecting technology on XLPE cable insulation has got great improvement. Based on summarizing the present technology on XLPE faults detection and reference the PD detection method on power transformer, this paper introduces a method on recognition PD mode of XLPE. This paper uses discharging quantum and stat. arithmetic operators of chart as inputs to artificial neural network. This paper introduces the development processing of cable, the reason to occur PD. And the detection methods present such as detection on transformer, mutual inductance, are synthesized. Demonstrate the importance of researching on XLPE cable PD measurement.The character of XLPE PD signal is analyzed, and measurement method is designed. Pulse current sensor is used to acquire PD signal by inducting pulse signal, and band-pass filter to exclude interfere. Several discharging models simulation are designed. Their PD signals are measured and measured cables are anatomized to observe their discharging trace.Implement of picking-up character and mode classifying are introduced, and expatiate the principle of artificial neural networks. Soft program is necessary to pick-up the character of PD signals and classify PD mode. Program to pick-up the character of PD signals is compiled. Using the discharging times and stat. operator on PRPD mode of PD signal, mode-classifying implements based on BPNN and SART are compiled.The artificial neural networks designed are applied to recognize measured signals. Conclusions are made: recognition rate of BPNN is 95%, and it is respect to magnitude of discharging signal and increases while signal magnitude increasing; The recognition rate of SART neural network is 98%, higher than that of BPNN, recognition rate increasing with the number of signal group. Then analyze the reason to fault recognition according to the recognition result.