| 电力变压器的智能故障诊断研究 |
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| 引用本文： | 乔维德,孙龙林.电力变压器的智能故障诊断研究[J].电气传动自动化,2010(5):48-51. |
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| 作者姓名： | 乔维德 孙龙林 |
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| 作者单位： | 1. 常州市广播电视大学,江苏常州,213001
2. 上海海洋石油局钻井分公司,上海,200000 |
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| 基金项目： | 江苏广播电视大学学术带头人基金资助项目 |
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| 摘 要： | 将基于改进遗传算法（IGA）和误差反向传播（BP）算法相结合构成的IGA-BP混合算法用于训练神经网络。该混合算法有效克服常规BP和传统GA算法独立训练神经网络的缺陷,并应用于电力变压器溶解气体分析的智能故障诊断。实验诊断结果表明,IGA-BP混合算法的收敛速度快于BP及GA算法,并且具有较高的诊断准确率。
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| 关 键 词： | 变压器 IGA-BP 神经网络 故障诊断 |
Research on intelligent fault diagnosis of power transformer |
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| QIAO Wei-de,SUN Long-lin.Research on intelligent fault diagnosis of power transformer[J].Electrical Drive Automation,2010(5):48-51. |
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| Authors: | QIAO Wei-de SUN Long-lin |
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| Affiliation: | QIAO Wei-de1,SUN Long-lin2(1.Changzhou Television & Radio University,Changzhou 213001,China,2.Shanghai Offshore Oil Bureau of Drilling Branch,Shanghai 200000,China) |
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| Abstract: | The hybrid algorithm based on improved genetic algorithm(IGA)and error backpropagation(BP)algorithm composed is used for training neural network.The hybrid algorithm IGA-BP can effectively overcome the defects which conventional BP and traditional GA algorithm train neural network independently and is applied in the intelligent fault diagnosis for dissolved gas analysis of power transformer.The experimental diagnosis results show that the convergence rate of IGA-BP algorithm is faster than BP and GA algorit... |
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| Keywords: | transformer IGA-BP neural network fault diagnosis |
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