Transformer fault acoustic identification model based on acoustic denoising and DBO-SVM

Author:

Lu LingORCID,Zhang Xin,Ma Hui,Pu Qiuping,Lu Yang,Xu Hongwei

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Reference23 articles.

1. Zhang H, Zhang G, Liu K et al (2022) Application and prospect of acoustic fingerprint detection technology in transformer fault diagnosis. Mech Res Appl 35(05):243–246

2. Mengyun W (2006) Statistical analysis of accidents and defects of 110(66)kV and above transformers in 2005. Power Equip 11:99–102

3. Guo J, Du L, Ji S et al (2011) Research on the application of transformer vibration model in short circuit fault. Shaanxi Electr Power 39(02):1–4

4. Yi L, Jiang G, Zhang G et al (2022) A fault diagnosis method of oil-immersed transformer based on improved Harris hawks optimized random forest. J Electr Eng Technol 17:2527–2540

5. Hwang D-H et al (2015) Support vector machine based bearing fault diagnosis for induction motors using vibration signals. J Electr Eng Technol Korea Inst Electr Eng 10(4):1558–1565

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