Study on transformer fault diagnosis technology of VMD local signal de-noising based on kurtosis - approximate entropy

• Autorzy: Chen Dingke , Mao Changbin , Qin Bin

Identyfikatory

DOI

10.29354/diag/118101

• Języki publikacji: EN

Abstrakty

EN

With the needs of social development, the scale of power equipment continues to expand. Among them, the transformer, as the core equipment in the power system, plays a key role in the safe and stable operation of the power system. However, in the field where the field strength is too high, partial breakdown of insulating media, that is the partial discharge occurs, which brings certain threats and damage to the safe operation of the power system. Therefore, this article uses the kurtosis-approximate entropy variational mode decomposition (VMD) partial discharge signal denoising method is used to preprocess the UHF partial discharge signal, through the simulation analysis and the result comparison, the feasibility of the method for denoising the partial signal of the transformer is clarified, designed to improve the safety and reliability of transformer operation.

Słowa kluczowe

EN

transformer; kurtosis; approximate entropy; variational mode decomposition; VMD

PL

transformator; diagnostyka uszkodzeń; kurtoza; entropia; niezawodność

• Wydawca: Polskie Towarzystwo Diagnostyki Technicznej
• Czasopismo: Diagnostyka
• Rocznik: 2020
• Tom: Vol. 21, No. 1
• Strony: 81--87
• Opis fizyczny: Bibliogr. 10 poz., wykr.

Twórcy

autor

Chen Dingke

• State Grid Chongqing Beibei Power Supply Company, Chongqing 400700, China

autor

Mao Changbin

• State Grid Chongqing Beibei Power Supply Company, Chongqing 400700, China

autor

Qin Bin

• State Grid Chongqing Beibei Power Supply Company, Chongqing 400700, China

Bibliografia

• 1. Chen XY. Research on gearbox vibration signal denoising and feature extraction method. Taiyuan University of Technology 2018.
• 2. Ding SY, Shen Q, Chen Y. Electrical diagnostic technology for partial discharge of power transformers. Science and Technology Outlook 2016; 26(33).
• 3. Dong J. Research and design of on-line monitoring system for partial discharge of power transformers. Transactions of Electrical Engineering 2017; (1): 22-25.
• 4. Ge XL. Research on online monitoring and fault diagnosis method of transformer based on DGA. Anhui University of Science and Technology 2018.
• 5. Luo XL. Research on Fault Diagnosis Technology of Transformer. Engineering Technology: Abstracts 2016.
• 6. Mi XY, Su BG, Zhang GS, et al. Discussion on Judging Method of Partial Discharge of Transformer. Transformer 2018; (4): 66-67.
• 7. Sun ZQ. Research on Partial Discharge Detection Technology of Electrical Equipment. Electronic Production 2018; (2).
• 8. Wang B. Research on Causes and Treatment Methods of Transformer Faults in Power System. Science and Technology Innovation and Application 2017; (34): 81-81.
• 9. Wang LL, Liu HL, Gao SG. Simulation Study on Propagation Characteristics of Partial Discharge Pulse Current in UHV Transformer. High Voltage Apparatus 2018; 54(11): 227-232.
• 10. Yan SY. Causes and Control Measures for Partial Discharge of Transformers. 2017 Annual Meeting of the Electrification Committee of China Railway Society and New Technology Seminar 2017.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).