| 基于振动信号和小波神经网络的变压器故障诊断 |
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| 引用本文： | 王春宁,朱跃光,马宏忠,赵宏飞,陈继宁.基于振动信号和小波神经网络的变压器故障诊断[J].电力技术,2014(4):75-79. |
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| 作者姓名： | 王春宁 朱跃光 马宏忠 赵宏飞 陈继宁 |
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| 作者单位： | [1]江苏省电力公司南京供电公司,江苏南京210008 [2]河海大学可再生能源发电技术教育部工程研究中心,江苏南京210098 [3]江苏省电力公司宿迁供电公司,江苏宿迁223800 |
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| 基金项目： | 国家电网公司总部重点科技项目（2011-0810-2251） |
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| 摘 要： | 提出一种基于振动信号和小波神经网络的电力变压器故障诊断方法.采用变压器油箱表面的振动信号作为采样信号进行频谱分析提取特征频率信号,并以此特征频率信号乘以电流标么值的平方作为训练样本进行小波神经网络训练,小波神经网络输出量能够反映出频谱特征向量和变压器故障类型之间的映射关系,从而实现变压器的故障诊断.实验结果表明,使用该方法能够有效地对变压器进行故障分类及其诊断,并且小波神经网络具有很好的泛化能力.
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| 关 键 词： | 电力变压器 故障诊断 小波神经网络 振动检测 |
Fault Diagnosis of Power Transformer Based on Vibration and Wavelet Neural Network |
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| Authors: | WANG Chun-ning ZHU Yue-guang MA Hong-zhong ZHAO Hong-fei CHEN Ji-ning |
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| Affiliation: | 1. Jiangsu Nanjing Power Supply Company, Nanjing 210008, China; 2. Research Center for Renewable Energy Generation Engineering, Hohai University, Ministry of Education, Nanjing 210098, China; 3. Jiangsu Suqian Power Supply Company, Suqian 223800, China) |
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| Abstract: | A fault diagnostic method of power transformer based on vibration and wavelet neural network is presented, which gets the characteristics of the vibration in frequency domain from the vibration sampled from the tank of transformers to train for the wavelet neural network （WNN）. With the output of the wavelet neural network, we can get the relationship between the faults and the frequency characteristics can be obtained. The experiment results show that the proposed method can be used for diagnosis of power transformer and output the type of the fault, and the wavelet neural has a good generalized performance. |
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| Keywords: | power transformer fault diagnosis wavelet neural network vibration detection |
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