Guogang YUAN, Zhushi RAO. Review of Non-electrical Quantity Monitoring and Fault Diagnosis for Power Transformer on Vibration Analysis Method[J]. Power Generation Technology, 2019, 40(2): 134-140.
DOI:
Guogang YUAN, Zhushi RAO. Review of Non-electrical Quantity Monitoring and Fault Diagnosis for Power Transformer on Vibration Analysis Method[J]. Power Generation Technology, 2019, 40(2): 134-140. DOI: 10.12096/j.2096-4528.pgt.18037.
Review of Non-electrical Quantity Monitoring and Fault Diagnosis for Power Transformer on Vibration Analysis Method
Vibration analysis method can realize condition monitoring and fault diagnosis of transformer without shutdown and disintegration
which is meaningful to improve the reliability of equipment operation. The vibration of transformer surface is closely related to the compaction state
displacement and deformation of transformer windings and cores
and has been extensively studied by domestic and foreign scholar. The numerical calculation and analysis methods and vibration testing techniques in vibration analysis was described. The application of signal processing methods in transformer vibration analysis was introduced in combination with fast Fourier transform (FFT)
wavelet
Hilbert-Huang transform (HHT) and blind source separation technology. The role of acoustic analysis methods in transformer abnormal conditions was expounded. The development of the test device was briefly described
mainly the on-line monitoring system and the basic analysis method of off-line vibrabion frequency response analysis(VFRA). According to the trend and difficulty of vibration analysis method in transformer diagnosis application
LavalleJ C.Failure detection in transformers using vibration analysis[D].MS Thesis, MIT, Cambridg, MA, USA, 1986.
Chung C, You C.Fault discrimination of power transformers using vibration analysis[C]//Proceedings of Integrating dynamics condition monitoring and controlling conference 21st Century, Balkema, Rotterdam, 1999: 523-529.
McCarthy D.An adaptive model for vibration monitoring of power transformers[M].The MIT Press, 1987.
Lee S.Modeling of winding vibration amplitude for diagnosis of power transformer[D].Soongsil University, Korea, 1994.
Kim H.A study on the adaptive noise cancellation of transformer vibration signal[D].Korea: Soongsil University, 1995.
Park S.Fault determination of power transformer by using analysis of vibration signal[D].Korea: Soongsil University, 1996.
Berler Z, Golubev A.Vibra-Acoustic method of transformer clamping pressure monitoring[C]//Conference Record of the 2000 IEEE International Symposium on Electrical Insulation, Anaheim, CA, USA, 2000: 263-266. https://www.researchgate.net/publication/3849268_Vibro-acoustic_method_of_transformer_clamping_pressure_monitoring .
Garcia B, Burgos J C, Alonso A M.Transformers tank vibration modeling as a method of detecting winding deformations-part Ⅰ:theoretical foundation[J].IEEE Transaction on Power Delivery, 2006(21):157-163.
Garcia B, Burgos J C, Alonso A M.Transformers tank vibration modeling as a method of detecting winding deformations-part Ⅱ:experimental verification[J].IEEE Transactions on Power Delivery, 2006(21):164-169, .
Patel M R.Dynamic response of power transformers under axial short circuit forces part Ⅱ-windings and clamps as a combined system[J].IEEE Transactions on Power Apparatus&Systems, 1973, PAS-92(5):1567-1576.
Lavalle J C.Failure detection in transformers using vibrational analysis[D].Massachusetts Institute of Technology, Boston, 1986.
Garcia B, Burgos J C, Alonso A.Winding deformations detection in power transformers by tank vibrations monitoring[J].Electric Power Systems Research, 2005, 74(1):129-138.
Garcia B, Burgos J C, Alonso A.Transformer tank vibration modeling as a method of detecting winding deformations-Part Ⅰ:Experimental verification[J].IEEE Transactions on Power Delivery, 2005, 21(1):157-163.
Mechefske K C.Assessing the internal mechanical integrity of power transformer using vibration tests[C]//Proceedings of ASME Joint Power Generator Conference, Houston, Texas, USA.1996: 953-958.
Sanzbobi M A, Garciacerrada A, Palacios R, et al.Experiences learned from the on-line internal monitoring of the behaviour of a transformer[C]//IEEE International Electric Machines & Drives Conference Record.IEEE, 1997. https://www.researchgate.net/publication/224262129_Experiences_learned_from_the_on-line_internal_monitoring_of_the_behaviour_of_a_transformer .
Bartoletti C, Desiderio M, Dicarlo D, et al.Vibro-acoustic techniques to diagnose power transformers[J].IEEE Transactions on Power Delivery, 2004, 19(1):221-229.
Huang N E, Shen Z, Long S R, et al.The empiricalmode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J].Proceedings of Royal Society of London, Series A, 1998:903-994.
Application and Challenges of Large Models in Power Industry
State Estimation and Fault Diagnosis of Proton Exchange Membrane Fuel Cells Based on Artificial Intelligence
Analysis of Key Technologies and Development Prospects for Renewable Energy-Powered Water Electrolysis for Hydrogen Production Based on Artificial Intelligence
Research on Fault Diagnosis Method of Photovoltaic Arrays Based on Improved Grey Wolf Algorithm Optimized Extreme Learning Machine
Bearing Faults Diagnosis Method Based on Stacked Auto-Encoder With Graph Regularization for Wind Turbines
Related Author
DING Zhengtao
WU Hao
TAO Zhiwei
YOU Yuan
ZHENG Jian
YAN Xinrong
GAO Xiang
LIN Da
Related Institution
Huadian Electric Power Research Institute Co., Ltd.
College of Energy Engineering, Zhejiang University
Shanghai KeLiang Information Technology Co., Ltd., Minhang District
Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 3GJ, United Kingdom
Department of Electrical and Electronic Engineering, Auckland University of Technology, Auckland 1010, New Zealand