气相色谱和神经网络在机车故障诊断中的应用
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摘要
为诊断电力机车变压器的故障类型,以提高铁路系统的安全性,提出了一种基于模糊控制的BP神经网络模型。首先应用气相色谱技术,分析变压器油中特征气体含量与故障之间的对应关系,确定电力机车变压器常见的故障类型;然后,收集各种故障类型数据,作为神经网络的训练样本数据和测试数据;最后,建立改进BP神经网络的诊断模型,实现测试数据的仿证测试。诊断结果表明,该模型在电力机车变压器故障诊断中具有良好的实用前景。
To diagnose the fault types of transformer of electric locomotive for improving the safety of railway system,the BP neural network model based on fuzzy control is proposed.Firstly,by adopting gas chromatograph technology,the correspondence between content of characteristic gases in transformer oil and faults are analyzed and the common faults of transformer of electric locomotive are determined.Then,various types of fault data are collected for using as the training sample data and test data of neural network.Finally,the improved BP neural network diagnosis model is established for realizing simulation testing.The diagnosis results verify that the model possesses excellent applicable prospects in fault diagnosis for transformer of electric locomotive.
To diagnose the fault types of transformer of electric locomotive for improving the safety of railway system,the BP neural network model based on fuzzy control is proposed.Firstly,by adopting gas chromatograph technology,the correspondence between content of characteristic gases in transformer oil and faults are analyzed and the common faults of transformer of electric locomotive are determined.Then,various types of fault data are collected for using as the training sample data and test data of neural network.Finally,the improved BP neural network diagnosis model is established for realizing simulation testing.The diagnosis results verify that the model possesses excellent applicable prospects in fault diagnosis for transformer of electric locomotive.
引文
[1]张德丰.MATLAB神经网络应用设计[M].北京:机械工业出版社,2009.
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[5]邵华平,张帆,湛运南.气相色谱法分析牵引变压器潜伏性故障[J].中国铁道科学,2001,22(4):36-39.
[6]刘杰,黄亚楼.基于BP神经网络的非线性网络流量预测[J].计算机应用,2007,27(7):1770-1772.
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[8]毛颖科,关志成,王黎明,等.基于BP人工神经网络的绝缘子泄露电流预测[J].中国电机工程学报,2007,27(27):7-12.
[9]杜文霞,吕锋,句希源.基于BP神经网络的电力变压器故障诊断[J].变压器,2007,44(3):45-47.
[10]徐程,邹金慧.BP神经网络在地震预测中的应用研究[J].自动化仪表,2012,33(6):12-14.
[2]傅荟璇,赵红.MATLAB神经网络应用设计[M].北京:机械工业出版社,2010.
[3]张代远.神经网络新理论与方法[M].北京:清华大学出版社,2006.
[4]李孟超,王允平,张洪波.变压器油气相色谱分析实用技术[M].北京:中国电力出版社,2010.
[5]邵华平,张帆,湛运南.气相色谱法分析牵引变压器潜伏性故障[J].中国铁道科学,2001,22(4):36-39.
[6]刘杰,黄亚楼.基于BP神经网络的非线性网络流量预测[J].计算机应用,2007,27(7):1770-1772.
[7]葛哲学,孙志强.神经网络理论与MATLAB R2007实现[M].北京:电子工业出版社,2007.
[8]毛颖科,关志成,王黎明,等.基于BP人工神经网络的绝缘子泄露电流预测[J].中国电机工程学报,2007,27(27):7-12.
[9]杜文霞,吕锋,句希源.基于BP神经网络的电力变压器故障诊断[J].变压器,2007,44(3):45-47.
[10]徐程,邹金慧.BP神经网络在地震预测中的应用研究[J].自动化仪表,2012,33(6):12-14.
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