| The on-line detection and location technology of cable partial discharge can reflect the insulation state of cable in time,which is of great significance to ensure the reliable operation of power supply network and realize the real state maintenance.Electromagnetic coupling method detects partial discharge signal by electromagnetic signal generated by HFCT coupled with PD signal,and it is the most commonly used on-line detection method for Cable Partial discharge.Multi-sensor measurement is a traveling wave location method based on high frequency current,which can effectively eliminate the influence of wave velocity uncertainty.However,the cable operation environment is complex,and the collected PD signal is seriously disturbed by noise,so that extracting the PD signal from the noisy signal and picking up its arrival time is the key to reliable location of PD fault.Therefore,this paper focuses on studies how to extract the partial discharge signal and pick up its arrival time with high accuracy under the environment of multiple noises.The transmission characteristics of PD signal in cable are the important theoretical basis for discharge measurement and reliable positioning of discharge source.The cable PD transmission model is built by using the special software PSCAD/EMTDC for transient analysis of power system.The simulation results show that when the PD signal is transmitted in the cable,the amplitude of the signal is attenuated due to the presence of resistance and conductance in the cable,and the phase of the signal is constantly changing due to the presence of inductance and capacitance,and the attenuation of the high-frequency component of the signal is more serious with the increase of transmission distance.The simulation results are consistent with the aforementioned theory,which verifies the rationality of the cable transmission model constructed,and lays the foundation for subsequent positioning analysis.Aiming at the influence of complex noise(mainly white noise and narrow-band interference)in the collection of PD signals,this paper proposes a de-noising algorithm based on CEEMDAN combined with wavelet packet.First,CEEMDAN was used to decompose the signals containing partial discharge,and the effective components were determined by calculating the correlation between components and the original signal.Then,SVD algorithm was used to suppress the narrow-band interference signals and frequency aliasing in the effective components.Then the wavelet packet threshold method is used to filter the remaining white noise in the effective component of the synthesis,so as to achieve the purpose of signal denoising.In order to verify the practicability of this algorithm,time-varying kurtosis method is used to pick up the denoised signal at the first arrival time.The simulation results show that the proposed method has low energy loss and low waveform distortion after denoising,and can make the pickup results at the first arrival of the local amplifier signal consistent with the manual pickup results when the background noise is-9db.In the PD localization algorithm based on multi-sensor,it is the key to improve the localization accuracy to accurately pick up the signal when it arrives at the sensor.In order to improve the adaptability of the pick up algorithm,a PD pick up algorithm based on improved Allen-Bear algorithm is proposed in this paper.Combining the advantages of the feature functions of Allen algorithm and Bear algorithm,the algorithm adds components representing the frequency domain to the original feature functions which only consider the time domain features.While ensuring the precision of picking up partial discharge signal at the time of arrival,the anti-interference capability of the algorithm is improved.Through the analysis of simulation and measured data,the proposed algorithm is proved to be better than the existing algorithm in terms of SNR,PD waveform and amplitude,time window length and PD position in the signal.It has practical engineering value. |
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