Partial Discharge Pattern Recognition in GIS Using External UHF Sensor
سال انتشار: 1402
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 81
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شناسه ملی سند علمی:
JR_JAREE-2-1_010
تاریخ نمایه سازی: 3 دی 1402
چکیده مقاله:
Partial Discharge (PD) measurement is one of the best solutions for condition assessment of Gas Insulated Switchgears (GISs). For having Condition-based maintenance of GIS, online PD monitoring is of great importance. For this aim, Ultra High Frequency (UHF) PD sensors should be installed inside the GIS during the installation. However, in most installed GISs in industries, the internal UHF PD sensors are not installed. In this paper, a new method for online defect type recognition according to external UHF PD sensors and based on the time-frequency representation of PD signal is proposed. In this case, four artificial defect types named protrusion on the main conductor, protrusion on the enclosure, free moving metal particle, and metal particle on spacer are implanted inside the ۱۳۲ kV L-Shaped structure of one phase in enclosure GIS. The signal energy at each level of the decomposed signal by Discrete Wavelet Transform (DWT) is applied for features of each defect type. The trends of signal energy variations at each frequency range of signal are applied for discriminating between each defect type. The Deep Feed Forward Network (DFFN) classifier is applied for PD pattern recognition. The results show the benefits and simplicity of the proposed method for PD signal classification, independent from the position of the PD sensor, especially in the case of online PD monitoring of GIS.
کلیدواژه ها:
Gas Insulated Switchgear (GIS) ، Partial Discharge (PD) ، Ultra High Frequency (UHF) measurements ، Pattern Recognition ، Time-frequency representation
نویسندگان
Reza Rostaminia
Electrical Engineering Department and Centre of Excellence in Power System Management and Control, Sharif University of Technology, Tehran ۱۴۵۸۸۸۹۶۹۴, Iran
Mehdi Vakilian
Electrical Engineering Department and Centre of Excellence in Power System Management and Control, Sharif University of Technology, Tehran ۱۴۵۸۸۸۹۶۹۴, Iran
Keyvan Firouzi
Electrical Engineering Department and Centre of Excellence in Power System Management and Control, Sharif University of Technology, Tehran ۱۴۵۸۸۸۹۶۹۴, Iran
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