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| The Fault Identification Method for Distribution Transformer based on Support Vector Machine Classification of Vibration Signal Characteristics |
| Wei Xiaoying1, Song Shijiang2, Guo Moufa1, Lu Guoyi3 |
1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350000;
2. Shaowu Electric Power Supply Company, State Grid Fujian Electric Power Co., Ltd, Shaowu, Fujian 354000;
3. Fuzhou Metro Co., Ltd, Fuzhou 350000 |
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Abstract The tank surface of distribution transformer contains a wealth of vibration signals from the iron core, which can directly reflect the working conditions of the core. Extracting the principal component of the core from vibration signals via Hilbert-Huang Transform (HHT) band-pass filter, and then the vibration signal is decomposed in time-frequency domain via the second band-pass filter of HHT, calculating the energy and center frequency of each sub-band reconstructed signal, which constitute the 2-D feature vector of the vibration signal. The vibration signal of the core in 4 typical conditions including normal states, two-point grounding, looseness and poor grounding are measured through no-load experiment, SVM classification is applied to these 2-D feature vectors. The result shows that the feature vector can represent each state of the core accurately and effectively.
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Published: 13 January 2016
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| Cite this article: |
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Wei Xiaoying,Song Shijiang,Guo Moufa等. The Fault Identification Method for Distribution Transformer based on Support Vector Machine Classification of Vibration Signal Characteristics[J]. Electrical Engineering, 2016, 17(1): 16-15.
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| URL: |
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https://dqjs.cesmedia.cn/EN/Y2016/V17/I1/16
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2016, Vol. 17 
