Chengjun Huang

Application of adaptive neuro fuzzy inference system to the partial discharge pattern recognition

The application of adaptive neuro fuzzy inference system (ANFIS) to the partial discharge (PD) pattern recognition is presented in this paper. Four types of defect models are made according to the main reason of insulation failures in real power system. Experiments are carried out to acquire the sample data, from which eight statistical features are extracted to construct the ANFIS. Different characteristics of the proposed defect models are compared based on the extracted features. Then the ANFIS is trained by characteristic features. Testing samples are utilized to validate the performance of the recognition system. The result shows that ANFIS reaches a successful recognition rate in the application of PD pattern classification.

Intelligent morphological filter applied to the signal processing of partial discharge for XLPE cable

Today the sensitive measurement of partial discharge (PD) signals in XLPE cable can be an important element for quality assurance and diagnostics in the factory and during the on-site test procedure. The results clearly indicate that PD analysis of XLPE cable is an excellent online tool to assess its dielectric condition. However, as the serious interference in-field, the acquired PD signals may be interrupted by periodic interferences and white noises, easily. This paper describes an intelligent morphological filter algorithm to remove the periodic pulse interference and white noise contained in the PD signals. The algorithm consists of two stages of morphological processing. The performance of the algorithm is evaluated with simulated and real PD signals. Compared with classical wavelet, there are substantial improvements in the indexes of average error, root mean square (rms) error and maximum error, especially in reducing distortion of the baseline waveform.

Investigation of PD electromagnetic wave characteristics in GIS

For exploring the characteristics of PD (partial discharge) electromagnetic wave (EM-wave) within gas insulated switchgear (GIS), the model for detecting PD electromagnetic wave signals in GIS was built and simulated in this paper. The characteristics of PD EM-wave were investigated in two aspects: excitation characteristic and propagation characteristic. The excitation characteristics of PD EM-wave are analyzed by changing the parameters of PD sources. The results show that the EM-wave signals which excited by PD sources are related with such factors as the radial angle Phi, waveform of discharge pulse, radial position of PD source. The propagation characteristics are calculated when PD EM-wave signal transited through the different component of GIS. The simulation results show that the signal was attenuated obviously when it propagated through insulator, L branch, and T branch. The attenuation of L branch is more serious than insulator and the attenuation of plumb way of T branch is most serious.