基于小波理论与LSSVM的模拟集成电路故障诊断方法
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摘要
随着微电子技术的发展，对集成电路故障诊断的需求日益迫切，通常一个微电子系统中，绝大部分故障通常来自模拟集成电路模块，据调查研究，在电子设备中90%以上的故障都来自模拟集成电路，随着集成电路技术的快速发展，电路的规模越来越大，诊断难度越来越高。模拟集成电路故障诊断方法的研究已经成为电路诊断领域中非常重要的研究课题，开展模拟集成电路故障诊断技术的研究，实现模拟集成电路故障诊断的自动化、智能化不仅具有重要的理论意义重大，而且有着很高的实用价值。由于模拟集成电路故障的多样性和复杂性，使得传统的故障诊断方法难以达到预期的诊断效果。对此，本文提出了基于小波理论与最小二乘支持向量机（LSSVM）的模拟集成电路故障诊断方法，提出了基于小波理论与LSSVM模拟集成电路故障诊断系统架构，并进行了基于小波理论的模拟集成电路诊断特征提取以及提出了基于LSSVM的模拟集成电路故障识别方法，最后提出了基于小波理论与LSSVM模拟集成电路故障诊断系统的实现方法。
论文的主要研究工作及成果如下：
1）针对当前模拟集成电路故障诊断系统中存在模拟集成电路故障特征提取精度低、模拟集成电路故障识别率低等问题，提出了基于小波理论与LSSVM模拟集成电路故障诊断系统架构，首先分析了模拟集成电路故障特性分析，在此基础上建立了基于小波理论与LSSVM模拟集成电路故障诊断系统架构。
2）提出了基于小波理论的模拟集成电路诊断特征提取方法，首先提出了小波变换理论，在此基础上建立了基于小波理论的模拟集成电路诊断特征提取模型，并进行了实例测试。
3）提出了基于LSSVM的模拟集成电路故障识别，首先介绍了最小二乘支持向量机分类器，提出了基于混沌粒子群优化算法的LSSVM参数优化方法，在此基础上，提出了基于最小二乘支持向量机的模拟集成电路故障识别模型，并进行了实例分析。
4）在研究基于小波理论与最小二乘向量机的模拟集成电路故障诊断方法关键技术的基础上，进行了基于小波理论与LSSVM模拟集成电路故障诊断系统实现方法研究，首先提出了基于小波理论与LSSVM模拟集成电路故障诊断系统的总体结构及其工作流程，介绍了此系统的功能模型，进行了基于小波理论与LSSVM模拟集成电路故障诊断模型的实现，最后进行了实例测试，实验结果表明本文设计的诊断系统的有效性。
With the development of the micro-electronics technique, it is urgent to fault diagnosisfor the integrated circuit.The faults of micro-electronics above90%come from theintegrated circuit.With the rapid development of the integrated circuit technique, the scale ofelectric circuit is bigger and biger,and diagnostic difficulty is higher and higher.The researchof fault diagnosis method of analogue integrated circuits has already become the importantresearch topic in the circuits diagnosis field. Fault diagnosis method of analogue integratedcircuits is performed to realize the automation and intelligence of fault diagnosis ofanalogue integrated circuits,which has a very high utility value.Because of diversity andcomplexity of the failures of analogue integrated circuits, traditional fault diagnosis methodis difficult to the expected diagnosis effects.Thus, fault diagnosis method of analogueintegrated circuits based on wavelet theory and least squares support vectormachine(LSSVM) is presented.Firstly,the structure of fault diagnosis system of analogueintegrated circuits based on wavelet theory and LSSVM is proposed in the thesis.Diagnostic characteristics extraction method of analogue integrated circuits based onwavelet theory is presented,and fault recognition of analogue integrated circuits based onLSSVM is presented.Finally, fault diagnosis system of analogue integrated circuits based onwavelet theory and LSSVM is developed.
Main research work and achievement of thesis are given as followings:
1) In order to solve the problems of the low precision of feature extraction and faultdiagnosis in the fault diagnosis for analogue integrated circuits,the structure of faultdiagnosis system of analogue integrated circuits based on wavelet theory and LSSVM ispresented.Firstly, fault characteristics of analogue integrated circuits are analyzed, thestructure of fault diagnosis system of analogue integrated circuits based on wavelet theoryand LSSVM is created according to the fault characteristics of analogue integrated circuits.
2) Diagnostic characteristics extraction method of analogue integrated circuits based onwavelet theory is presented. Firstly, wavelet theory is introduced. Then,diagnosticcharacteristics extraction model of analogue integrated circuits based on wavelet theory isestablished. The case is used to test the diagnostic characteristics extraction method.
3) Fault recognition of analogue integrated circuits based on LSSVM is presented.Firstly, least squares support vector machine classifier is introduced,and parameteroptimization of LSSVM based on chaos particle swarm optimization algorithm is presented,fault recognition model of analogue integrated circuits based on LSSVM is presented,and the case is analyzed.
4) In the basis of key technologies of fault diagnosis for analog integrated circuitsbased on wavelet theory and least squares support vector machine,fault diagnosis system ofanalogue integrated circuits based on wavelet theory and LSSVM is developed. Firstly,overall structure and workflow of fault diagnosis system of analogue integrated circuitsbased on wavelet theory and LSSVM is given,the functional model of the system isintroduced, fault diagnosis model of analogue integrated circuits based on wavelet theoryand LSSVM is realized.Finally,the cases are used to test the model.The experimental resultsshow that the diagnosis system is effective.
论文的主要研究工作及成果如下：
1）针对当前模拟集成电路故障诊断系统中存在模拟集成电路故障特征提取精度低、模拟集成电路故障识别率低等问题，提出了基于小波理论与LSSVM模拟集成电路故障诊断系统架构，首先分析了模拟集成电路故障特性分析，在此基础上建立了基于小波理论与LSSVM模拟集成电路故障诊断系统架构。
2）提出了基于小波理论的模拟集成电路诊断特征提取方法，首先提出了小波变换理论，在此基础上建立了基于小波理论的模拟集成电路诊断特征提取模型，并进行了实例测试。
3）提出了基于LSSVM的模拟集成电路故障识别，首先介绍了最小二乘支持向量机分类器，提出了基于混沌粒子群优化算法的LSSVM参数优化方法，在此基础上，提出了基于最小二乘支持向量机的模拟集成电路故障识别模型，并进行了实例分析。
4）在研究基于小波理论与最小二乘向量机的模拟集成电路故障诊断方法关键技术的基础上，进行了基于小波理论与LSSVM模拟集成电路故障诊断系统实现方法研究，首先提出了基于小波理论与LSSVM模拟集成电路故障诊断系统的总体结构及其工作流程，介绍了此系统的功能模型，进行了基于小波理论与LSSVM模拟集成电路故障诊断模型的实现，最后进行了实例测试，实验结果表明本文设计的诊断系统的有效性。
With the development of the micro-electronics technique, it is urgent to fault diagnosisfor the integrated circuit.The faults of micro-electronics above90%come from theintegrated circuit.With the rapid development of the integrated circuit technique, the scale ofelectric circuit is bigger and biger,and diagnostic difficulty is higher and higher.The researchof fault diagnosis method of analogue integrated circuits has already become the importantresearch topic in the circuits diagnosis field. Fault diagnosis method of analogue integratedcircuits is performed to realize the automation and intelligence of fault diagnosis ofanalogue integrated circuits,which has a very high utility value.Because of diversity andcomplexity of the failures of analogue integrated circuits, traditional fault diagnosis methodis difficult to the expected diagnosis effects.Thus, fault diagnosis method of analogueintegrated circuits based on wavelet theory and least squares support vectormachine(LSSVM) is presented.Firstly,the structure of fault diagnosis system of analogueintegrated circuits based on wavelet theory and LSSVM is proposed in the thesis.Diagnostic characteristics extraction method of analogue integrated circuits based onwavelet theory is presented,and fault recognition of analogue integrated circuits based onLSSVM is presented.Finally, fault diagnosis system of analogue integrated circuits based onwavelet theory and LSSVM is developed.
Main research work and achievement of thesis are given as followings:
1) In order to solve the problems of the low precision of feature extraction and faultdiagnosis in the fault diagnosis for analogue integrated circuits,the structure of faultdiagnosis system of analogue integrated circuits based on wavelet theory and LSSVM ispresented.Firstly, fault characteristics of analogue integrated circuits are analyzed, thestructure of fault diagnosis system of analogue integrated circuits based on wavelet theoryand LSSVM is created according to the fault characteristics of analogue integrated circuits.
2) Diagnostic characteristics extraction method of analogue integrated circuits based onwavelet theory is presented. Firstly, wavelet theory is introduced. Then,diagnosticcharacteristics extraction model of analogue integrated circuits based on wavelet theory isestablished. The case is used to test the diagnostic characteristics extraction method.
3) Fault recognition of analogue integrated circuits based on LSSVM is presented.Firstly, least squares support vector machine classifier is introduced,and parameteroptimization of LSSVM based on chaos particle swarm optimization algorithm is presented,fault recognition model of analogue integrated circuits based on LSSVM is presented,and the case is analyzed.
4) In the basis of key technologies of fault diagnosis for analog integrated circuitsbased on wavelet theory and least squares support vector machine,fault diagnosis system ofanalogue integrated circuits based on wavelet theory and LSSVM is developed. Firstly,overall structure and workflow of fault diagnosis system of analogue integrated circuitsbased on wavelet theory and LSSVM is given,the functional model of the system isintroduced, fault diagnosis model of analogue integrated circuits based on wavelet theoryand LSSVM is realized.Finally,the cases are used to test the model.The experimental resultsshow that the diagnosis system is effective.
引文
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