Partial Discharge Pattern Recognition Of Transformer Based On Electric Signal And Ultrasonic Comprehensive Analysis

Partial Discharge Pattern Recognition for the timely detection of potential failures, to prevent the occurrence of major accidents power system is important. PD pattern recognition in the current transformers are electrical pulse method and gas chromatography. Because the field a strong electromagnetic interference and the complex internal structure of the transformer, electric pulse method of identifying the effect is not ideal. Gas chromatography from electromagnetic interference, high recognition accuracy, but there is a serious lag is not conducive to timely detection of potential failures.Transformer partial discharge by the ultrasonic signal generated by electromagnetic interference is small, but the band is narrow, the waveform is complex and susceptible to influence the internal structure of the transformer. In-depth analysis of electrical pulse signals and ultrasound signals based on their own characteristics, this paper presents a comprehensive analysis based on electro-acoustic partial discharge pattern recognition method, and the establishment of the Experimental Analysis of hardware and software systems.First, according to the principle and characteristics of partial discharges, the establishment of five discharge of transformer model, set up a partial discharge test system. Including measurement subsystem, coupled subsystem, transport subsystem and the experimental system schematic and wiring diagram.Second, common space for the experimental system interference, power disturbances and interfere with and affect the grounding resistance, the corresponding hardware are given disincentives and software destructive interference method. Software method using wavelet-based algorithm to eliminate interference and destructive interference with the Fourier method were compared.Then, the analysis of transformer partial discharge location method of electrical characteristics and disadvantages of various positioning methods and the sound of acoustic location method; extract the electrical pulse signal characteristics and the ultrasonic signal in time domain statistical features, build feature vectors, to achieve a typical Discharge pattern recognition.Finally, the development of the transformer partial discharge analysis system, including data acquisition and display, wavelet transform and Fourier transform destructive interference, ultrasound and discharge pattern recognition and other software modules.