基于SVM专家系统的模拟电路PCB故障诊断研究
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摘要
针对基层部队电子装备中模拟电路的故障识别问题,以及传统专家系统推理机的"匹配冲突",以某型飞机航空电源发电系统为研究对象,提出了基于支持向量机(SVM)的专家系统推理机构建方法。该电源发电系统由发动机、恒速装置、永磁发电机、调压器、旋转整流器等部分组成。通过在推理机中嵌入SVM来实现对电机设备中印制电路板(PCB)模块的故障诊断。对故障数据进行预处理和SVM训练,最终通过实测数据样本来验证故障诊断的有效性。实验仿真结果表明,该方法有效提高了专家系统故障诊断的检测率和故障识别效率。
Aimed at the problem of analog circuit fault identification in the electronics of grassroots units and the problem of"match conflict"in the traditional expert system inference engine,it proposes an SVM-based reasoning engine construction method by embedding SVM into the inference engine fault diagnosis of printed circuit board(PCB)module in equipment.Experimental results show that the proposed method can effectively improve the identification efficiency and correctness of expert system fault diagnosis.
Aimed at the problem of analog circuit fault identification in the electronics of grassroots units and the problem of"match conflict"in the traditional expert system inference engine,it proposes an SVM-based reasoning engine construction method by embedding SVM into the inference engine fault diagnosis of printed circuit board(PCB)module in equipment.Experimental results show that the proposed method can effectively improve the identification efficiency and correctness of expert system fault diagnosis.
引文
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[10]张奎,王建南,王肖峰.基于神经网络的变压器故障诊断[J].电子测量技术[J].2017,40(12):98-101.
[11]LUO J,MENG CH,SU ZH ZH.Design of fault diagnosis expert system based on relation database[J].Electrical Measurement&Instrumentation,2002,39(7):37-39.
[12]韩力群,施彦.人工神经网络理论及应用[D].北京:机械工业出版社,2016.
[13]单燕,李玲娟,孙杜靖.基于主成分分析的并行化数据流降维算法研究[J].南京邮电大学学报(自然科学版)2015,35(5):99-104.
[14]吴祎,王友仁,陈妤,等.基于BPNN的故障诊断方法[J].电子测量与仪器学报,2012,26(5):458-462.
[15]刘勇,许爱强.基于免疫机理的航空装备智能故障诊断技术研究[D].烟台:海军航空大学,2011:119-120.
[16]王文靖,梁旭,温菲菲.无人机机载发电机的故障诊断技术研究[J].国外电子测量技术,2016,35(8):94-98.
[2]李红卫,杨东升,孙一兰,等.智能故障诊断技术研究综述与展望[J].计算机工程与设计,2013,34(2):632-637.
[3]王亚南.专家系统中推理机制的研究与应用[D].武汉:武汉理工大学,2006.
[4]Translated by YIN J,CHEN Y Q,LIU X CH,et al.Expelt System:Principle&Programming[M].Beijing:China Machine Press,2006.
[5]ZHANG J Y,ZHANG W,In telligent diagnosis and prediction of equipment faults[J].Beijing:National Defense Industry Press,2013.
[6]盛兆顺,尹琦岭.设备状态监测与故障诊断技术及应用[M].背景:化学工业出版社,2003.
[7]ZHENG X D.Application of neural network and expert system in fault diagnosis of radar equipment[J].Nanjing University of Science and Technology,1999:32-51.
[8]黄玲玲,刘三阳,高卫峰.具有人工蜂群搜索策略的差分进化算法[J].控制与决策,2012,27(11):1644-1648.
[9]张欢,邓志良.基于模糊推理的摊铺机故障诊断专家系统[J].微计算机信息,2007:221-222.
[10]张奎,王建南,王肖峰.基于神经网络的变压器故障诊断[J].电子测量技术[J].2017,40(12):98-101.
[11]LUO J,MENG CH,SU ZH ZH.Design of fault diagnosis expert system based on relation database[J].Electrical Measurement&Instrumentation,2002,39(7):37-39.
[12]韩力群,施彦.人工神经网络理论及应用[D].北京:机械工业出版社,2016.
[13]单燕,李玲娟,孙杜靖.基于主成分分析的并行化数据流降维算法研究[J].南京邮电大学学报(自然科学版)2015,35(5):99-104.
[14]吴祎,王友仁,陈妤,等.基于BPNN的故障诊断方法[J].电子测量与仪器学报,2012,26(5):458-462.
[15]刘勇,许爱强.基于免疫机理的航空装备智能故障诊断技术研究[D].烟台:海军航空大学,2011:119-120.
[16]王文靖,梁旭,温菲菲.无人机机载发电机的故障诊断技术研究[J].国外电子测量技术,2016,35(8):94-98.