Research on Transformer Core Loosening Fault Diagnosis Based on VMD
In order to accurately extract the characteristic frequency of the vibration signal of the transformer core, a fault diagnosis method based on variational mode decomposition (VMD) and sparse decomposition is proposed for the non-linear, non-stationary and low signal-to-noise ratio of the vibration signal of transformer core. The fundamental frequency (100 Hz) and some frequency doubling components are included in the vibration signal of the transformer core. After the failure of the transformer core, the characteristic frequency in the vibration signal of the core also changes. Firstly, the signal is sparsely decomposed and denoised, and the noise-reduced signal is subjected to VMD decomposition. Then, the characteristic components are selected from the decomposed components for spectrum analysis. Finally, the state of the core is detected.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9789811528613
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Supplemental Notes:
- © Springer Nature Singapore Pte Ltd. 2020.
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Corporate Authors:
Springer Singapore
152 Beach Road
Singapore, 189721 -
Authors:
- Liu, Yuzhi
- Zhai, Kuankuan
- Kang, Xiaorui
- Guo, Wei
- Zhang, Xinyu
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Conference:
- 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT 2019)
- Location: Qingdao , China
- Date: 2019-10-25 to 2019-10-27
- Publication Date: 2020-4
Language
- English
Media Info
- Media Type: Web
- Edition: 1
- Features: References;
- Pagination: pp 671-682
- Monograph Title: Proceedings of the 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019: Novel Traction Drive Technologies of Rail Transportation
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Serial:
- Lecture Notes in Electrical Engineering
- Volume: 638
- Publisher: Springer
- ISSN: 1876-1100
Subject/Index Terms
- TRT Terms: Decomposition; Fault monitoring; Spectrum analysis; Transformers; Vibration tests
- Subject Areas: Energy; Railroads;
Filing Info
- Accession Number: 01926522
- Record Type: Publication
- ISBN: 9789811528613
- Files: TRIS
- Created Date: Aug 6 2024 9:03AM