基于小波神经网络的模拟电路故障诊断方法研究及系统实现
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摘要
电子设备的故障大多出自模拟电路。随着电子工业迅速发展,电子设备的结构日益复杂,对模拟电路故障诊断的要求不断提高,对模拟电路故障诊断方法的研究也更具现实意义。因其自身存在许多困难,传统的故障诊断方法很难达到预期的效果,具有非线性映射特性的神经网络为模拟电路故障诊断提供了一条有效途径,本文研究了将小波分析与神经网络结合的模拟电路故障诊断方法。
本文首先在分析模拟电路故障诊断基本思想的基础上,阐述了神经网络故障诊断的原理,探讨了用于故障诊断的BP网络的设计方法。然后,研究了将小波分析与神经网络结合用于模拟电路故障诊断的方法,松散型的结合通过小波分解输出信号提取各频段的能量作为故障特征输入到神经网络训练,紧致型的结合则将神经网络中的激励函数用特性良好的小波函数代替,通过对带通滤波器电路诊断的实例证明了小波神经网络方法的有效性、优越性。最后将虚拟仪器技术引入到模拟电路故障诊断领域,以负反馈放大器电路为例,设计完成基于LabVIEW的故障诊断系统,可实现故障的诊断和故障类型的显示,界面直观。
总之,基于小波神经网络的方法对解决模拟电路故障诊断问题是切实有效的,将虚拟仪器技术应用到模拟电路故障诊断系统中,有很好的工程应用前景。
Most of the electronic equipment failure is caused by analog circuit fault. with the development of electronic industry, requirements on analog circuit fault diagnosis become higher, so research of methods of analog circuit fault diagnosis is significative. For itself with many difficulties existing, traditional methods of fault diagnosis are hard to achieve the desired results. Neural Networks,which have nonlinear mapping and generalizing ability, provide a powerful way to diagnose faults of analog circuits, morever, methods of combining Wavelet Transform and Neural Network can better deal with some critical problems in analog circuit fault diagnosis.
Firstly, this paper illustrates the principle of Neural Network fault diagnosis after understanding basic analog circuit fault diagnosis theories, elaborates approaches of designing BP Network for fault diagnosis. Secondly, this paper researches methods of conbining Wavelet Transform with Neural Network for analog circuit fault diagnosis. for the loose method, using Wavelet decomposition to process the impulse response drastically reduce the number of input fed to the Neural Network, for the compactive method, Wavelet function is used as neural network's inspirit function because of it's good performance, and simulation result indicates that the two methods are feasible and effective by diagnosing a Band-pass filter. Finally, virtual instrument technology is introduced in the area of analog circuit fault diagnosis, LabVIEW procedures are designed to accomplish a fault diagnosis system for an example of negative feedback amplifier circuit, the system can diagnose fault and show fault types intuitively.
In a word, the Wavelet Neural Network based approches for fault diagnosis of analog circuits are practical and effective, application of virtual instrumentation to the analog circuit fault diagnosis system, have a good engineering application prospect.
本文首先在分析模拟电路故障诊断基本思想的基础上,阐述了神经网络故障诊断的原理,探讨了用于故障诊断的BP网络的设计方法。然后,研究了将小波分析与神经网络结合用于模拟电路故障诊断的方法,松散型的结合通过小波分解输出信号提取各频段的能量作为故障特征输入到神经网络训练,紧致型的结合则将神经网络中的激励函数用特性良好的小波函数代替,通过对带通滤波器电路诊断的实例证明了小波神经网络方法的有效性、优越性。最后将虚拟仪器技术引入到模拟电路故障诊断领域,以负反馈放大器电路为例,设计完成基于LabVIEW的故障诊断系统,可实现故障的诊断和故障类型的显示,界面直观。
总之,基于小波神经网络的方法对解决模拟电路故障诊断问题是切实有效的,将虚拟仪器技术应用到模拟电路故障诊断系统中,有很好的工程应用前景。
Most of the electronic equipment failure is caused by analog circuit fault. with the development of electronic industry, requirements on analog circuit fault diagnosis become higher, so research of methods of analog circuit fault diagnosis is significative. For itself with many difficulties existing, traditional methods of fault diagnosis are hard to achieve the desired results. Neural Networks,which have nonlinear mapping and generalizing ability, provide a powerful way to diagnose faults of analog circuits, morever, methods of combining Wavelet Transform and Neural Network can better deal with some critical problems in analog circuit fault diagnosis.
Firstly, this paper illustrates the principle of Neural Network fault diagnosis after understanding basic analog circuit fault diagnosis theories, elaborates approaches of designing BP Network for fault diagnosis. Secondly, this paper researches methods of conbining Wavelet Transform with Neural Network for analog circuit fault diagnosis. for the loose method, using Wavelet decomposition to process the impulse response drastically reduce the number of input fed to the Neural Network, for the compactive method, Wavelet function is used as neural network's inspirit function because of it's good performance, and simulation result indicates that the two methods are feasible and effective by diagnosing a Band-pass filter. Finally, virtual instrument technology is introduced in the area of analog circuit fault diagnosis, LabVIEW procedures are designed to accomplish a fault diagnosis system for an example of negative feedback amplifier circuit, the system can diagnose fault and show fault types intuitively.
In a word, the Wavelet Neural Network based approches for fault diagnosis of analog circuits are practical and effective, application of virtual instrumentation to the analog circuit fault diagnosis system, have a good engineering application prospect.
引文
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[2]杨士元.模拟系统的故障诊断与可靠性设计.北京：清华大学出版社,2001.11.
[3]Berkowitz R.S. Condition for Network-element-value Solvability. IRE Trans. Circuits Theory,1962,15(9):25-29.
[4]Navid N, Willson Jr. A theory and algorithm for analog circuit fault diagnosis. IEEE Transaction on Circuits and Systems,1979,26(7):440-457.
[5]Salama A, Starzyk J, Bandler J. A unified decomposition approach for fault location in large analog circuits. IEEE Transaction on Circuits and Systems,1983, 30(5):257-256.
[6]Cabral E F Jr, Teruya M Y, Soria R A B. Using MLPs for fault analysis in analog circuits. Proceeding of the 38th Midwest Symposium on Circuits and Systems,1995, 2:1172-1174.
[7]Fanni A, Giua A, Marchesi M, et al. A neural network diagnosis approach for analog circuits. Applied Intelligence,1999,11(2):169-186.
[8]Mohammadi K, Monfared A R M, Nejad A M. Fault diagnosis of analog circuits with tolerance by using RBF and BP neural networks. Student Conference on Research and Development,2002,317-321.
[9]Catelani M, Fort A, Nosi G. Application of radial basis function network to the preventive maintenance of electronic analog circuits. Proceeding of the 16th IEEE Instrumentation and Measurement Technology Conference,1999,1:510-513.
[10]Contu S, Fanni A, Marchesi M, et al. Wavelet analysis for diagnostic problems.8th Mediterranean Electrotechnical Conference,1996,3:1571-1574.
[11]陈圣俭,洪炳荣,王月芳.可诊断容差模拟电路的软故障的新故障字典法.电子学报,2000,28(2)：127-1129.
[12]谭阳红,何怡刚.模拟电路故障诊断的新故障字典法.微电子学,2001,31(4)：252-254.
[13]孙义闯,林在旭.非线性电路故障诊断的似故障增量电路法.电子学报,1987,15(5)：82-88.
[14]吴耀,童诗白.线性电路K故障诊断法的有效范围.电子科学学刊,1989,2(11)：113-120.
[15]沈谦,张良震.BP网络改进及在模拟电路故障诊断中的应用.微电子学与计算机,1996,13(1)：37-40.
[16]尉乃红,杨士元,童诗白.基于BP网络的线性电路故障诊断.计算机学报,1997,20(4)：360-366.
[17]何怡刚.非线性容差模拟电阻电路故障诊断神经网络方法.固体电子学研究发展,2002,22(3)：297-299.
[18]陶峰,李春明,刘利强.基于模糊神经网络的模拟电路故障诊断系统的研究.内蒙古工业大学学报(自然科学版),2003,22(3)：218-222.
[19]谢宏,何怡刚,吴杰.小波变换在模拟电路故障诊断中的应用.数学理论与应用,2001,21(3)：96-98.
[20]王淑娟,陈博,赵国良.基于小波包变换预处理的模拟电路故障诊断方法.电工技术学报,2003,18(4)：118-122.
[21]韩宝如,孟玲玲.紧致型小波神经网络在模拟电路故障诊断中的应用.现代电子技术,2006,231(16)：145-149.
[22]吕敬祥,彭敏放,曹铁军.遗传BP网络在模拟电路故障诊断的应用.自动化与仪表,2005,20(1)：4-6.
[23]谭阳红,何怡刚,陈洪云等.大规模电路故障诊断神经网络方法.电路与系统学报,2001,6(4)：25-28.
[24]谭阳红,何怡刚,陈洪云.大规模电路故障诊断的集团法.电子测量与仪器学报,2003,17(4)：57-62.
[25]Mehran Aminian, Farzan Aminian. Neural-network based analog-circuit fault diagnosis using wavelet transform as preprocessor[J]. IEEE Transaction on Circuits and System II:Analog and Digital Signal Processing,2000,47(2):151-156.
[26]Anna Wang,, Junfang Liu et al. Algorithms Comparison of Feature Extraction and Multi-class Classification for Fault Diagnosis of Analog Circuit[C]. Proceedings of 2007 International Conference on Wavelet Analysis and Pattern Recognition,2007: 566-572.
[27]Zhang Qinghua, Benvenist Albert. Wavelet networks. IEEE Trans On Neural Network,1992,3(6):889-898.
[28]黄天成,马世纪,罗志华.基于小波网络的水轮机组故障诊断.中国仪器仪表,2004,04：33-36.
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