A generalized fault diagnosis method in dynamic analogue circuits

Fault diagnosis of analogue circuits is essential for analogue and mixed‐signal systems testing and maintenance. A new method is proposed in this paper for multiple fault diagnosis of linear analogue circuits in frequency domain. The Woodbury formula is applied to the modified nodal equation to construct the fault diagnosis equation, which relates the limited measured circuit responses with the multiple faults inside the circuit in a linear way. A recently developed ambiguity group locating technique is modified here to identify the faulty parameters directly. Computation cost is reduced compared to combinatorial search in traditional fault verification methods. Only one node is needed for voltage measurement, but multiple excitations on accessible nodes are required for fault identification. Parameter evaluation can provide the exact solution to the deviated values of faulty parameters. The faulty parameter deviations can have any finite values. Example circuits are provided to illustrate the proposed method. Two other methods for multiple analogue fault diagnosis sharing the same mechanism as the method proposed in this paper are also briefly described. The proposed method is extremely effective for the circuit with very limited accessible nodes and is also computationally efficient. Copyright © 2002 John Wiley & Sons, Ltd.     

An algorithm for multiple fault diagnosis in analogue circuits

The paper deals with multiple fault diagnosis of analogue AC or DC circuits with limited accessible terminals for excitation and measurement and brings an algorithm for identificating faulty elements and evaluating their parameters. The main achievement is a method enabling us to efficiently identify faulty elements. For this purpose some testing equations are derived playing a key role in identification of possibly faulty elements which are next verified using a test of acceptance. The proposed approach is described in detail for double fault diagnosis. Also extension to triple fault diagnosis is given. Although the method pertains to linear circuits, some aspects of multiple fault diagnosis of non‐linear circuits can be also performed using the small signal approach. Two numerical examples illustrate the proposed method and show its efficiency. Copyright © 2006 John Wiley & Sons, Ltd.     

一种基于 DSP的电力电子电路在线故障诊断方法

以三相桥式整流电路为例,首先对可控整流装置正常工作和故障运行时整流电压波形进行分析和归类,定义了一种"面积"并建立了故障模型,提出了一种改进的谱分析故障诊断方法,根据其特征值进行诊断定位;其次归纳出实验算法并用 DSP系统实现,实验表明该方法实现了可控整流装置的在线故障诊断和监测;最后总结了该方法的特点并推广至其它形式整流电路.     

基于小波神经网络的模拟电路故障诊断改进

在运用神经网络进行模拟电路故障诊断的过程中,代表着故障特征的网络输入至关重要,由于小波变换的时频局部化和多尺度分析等特性,将两者结合起来,通过小波变换对模拟电路的输出响应进行故障特征提取,同时解决PSPICE与MATLAB之间的数据通信问题,提出将蒙特卡罗分析产生的所有训练样本经过处理后输入到一个神经网络进行训练的方法,从而避免了训练多个神经网络。利用神经网络对各种故障模式进行分类,实现模拟电路的故障诊断,并进一步与传统的BP网络故障诊断法进行比较。仿真结果表明,该方法可以实现故障检测及定位,诊断的准确率显著提高,适用于模拟电路故障诊断。     

Multiple catastrophic fault diagnosis of analog circuits considering the component tolerances

This paper deals with the diagnosis of multiple catastrophic faults, being cuts (open‐circuits) of some connecting paths and/or short‐circuits of some pairs of points in analog circuits. A method enabling us to detect and identify the faults, taking into account the deviations of the circuit parameters within their tolerance ranges, is developed. The method exploits an appropriate fault dictionary. The fault dictionary is used only for preliminary identification of the faults, because it is based on the analysis of the circuits with nominal parameters. The crucial point of the method is a verification procedure, proposed in this paper, based on the linear programming approach. It leads to the results considering the component variations within their tolerance ranges. In addition, a procedure for selecting appropriate test points, employing some evolutionary techniques, is developed. Although the approach presented in this paper is described in detail for linear circuits, it can be directly generalized to nonlinear circuits. Three numerical examples, including two linear and one nonlinear circuits, illustrate the proposed method and show its efficiency. Copyright © 2011 John Wiley & Sons, Ltd.     

模拟电路的马氏距离故障诊断方法研究

针对欧氏距离在模拟电路故障诊断中的不足,提出模拟电路的马氏距离故障诊断方法。利用MULTISIM对电路的软故障和硬故障进行仿真获取故障特征样本,在MATLAB中计算样本与故障类之间的马氏距离,并选择距离最小的故障类作为诊断结果。仿真结果表明:在20次不同特征维数的试验中,欧氏距离,正规化欧氏距离和马氏距离故障诊断方法的平均诊断准确率分别为:86.7%,87.1%和92.9%。马氏距离的诊断方法不受特征相关性的影响,能够正确诊断出欧氏距离和正规化欧氏距离诊断方法的误诊样本,在模拟电路的故障诊断中的准确率更高。     

大规模容差模拟电路多故障诊断法

本文研究了大规模容差模拟电路的多故障诊断问题,针对交流、直流线性电路和非线性直流电路,考虑了测试点数目有限以及元件容差存在的情况下的电路故障诊断,采用了一种基于线性程序概念的子网络级故障诊断算法来确定元件的实际参数是否在容差范围内或者某些元件是否有故障.文中提及的几个测试方程在定义可能的故障元件中起了关键性作用,并详细阐述了二重故障的诊断原理,且给出了三重故障的诊断公式.该方法大大减少了大规模网络故障诊断计算量,快速有效的定位故障元件.最后用实例说明了该法的有效性.     

基于粗糙集-神经网络系统的电力电子电路故障诊断

基于粗糙集理论RST(Rough Set Theory)与BP神经网络系统,提出了电力电子电路故障诊断的方法：粗糙集-神经网络系统相结合的方法。叙述了粗糙集-神经网络系统诊断电力电子电路的过程。以三相可控整流电路为例,对故障信息中样本的故障征兆进行数据预处理,通过知识约简,形成诊断的确定性规则,实现故障分类;然后将粗糙集的分类结果与故障信息中的输出电压Ud采样值作为神经网络的输入,实现故障元的定位。仿真实例表明,该方法不仅准确可靠,而且提高了系统诊断的速度。     

联合VMD与ISSA-ELM的电力电子电路软故障诊断

针对电力电子电路的软故障特征区分度差、不易诊断等问题,提出了变分模态分解(VMD)结合改进的麻雀搜索算法(ISSA)优化极限学习机(ELM)的故障诊断方法。首先,将采集的故障信号进行VMD分解成本征模态分量(IMF),提取线性重构后IMF的12维时域参数作为故障诊断的特征向量。其次为提高ELM在故障诊断中的精度,提出ISSA对ELM的参数进行优化,建立ISSA-ELM分类模型。ISSA首先采用Iterative映射初始化种群,然后在发现者位置更新处引入自适应惯性权重因子,最后在解的位置引入Levy变异算子进行扰动得到新解等3种策略改进,提高算法性能。在8类基准函数测试中,ISSA比另外4种智能算法的收敛速度和寻优精度均有提升,并且VMD结合ISSA-ELM在功率为150 W Boost电路软故障诊断中精度达到99%以上。     

数模混合电路故障诊断方法的现状

本文针对数模混合电路故障诊断技术的发展现状，对几种常见的方法进行了总结，说明了各方法的基本原理，并分析了各自的优缺点。最后简要介绍了数模混合电路故障诊断技术在实际中的应用，并对它的发展趋势进行了预测。研究表明目前还没有成熟的数模混合电路系统的故障诊断的方法。     

Non‐linear analog circuit fault diagnosis with large change sensitivity

Large change sensitivity has been proved efficient at, but restricted to, generating a linear circuit fault dictionary. This paper discusses the extension of large change sensitivity to non‐linear analog circuit fault diagnosis. The fault dictionary is divided into d.c. and a.c. sections. In the d.c. domain, non‐linear components are approximated with piecewise linear models. By relating the operating region of each piecewise linear model to the magnitude of a single fault in a procedure termed preconditioning, it is shown that large change sensitivity can efficiently compute the response of a faulty non‐linear circuit. Results presented of an analysis of computational complexity show a significant reduction in the cost of simulating single linear resistor faults in a non‐linear circuit using this method. In addition, after establishing that the resistive portion of the circuit is fault free, a fault dictionary is constructed for dynamic components using large change sensitivity in the small signal a.c. domain. Included with a discussion on the issues of large change sensitivity based simulation‐before‐test, a small non‐linear circuit is used to demonstrate the effectiveness of the proposed fault diagnosis algorithm. Copyright © 2000 John Wiley & Sons, Ltd.     

DC tolerance analysis of electronic circuits by polyhedral circuits

Real equilibrium solutions of electronic circuits are affected by deviation of real characteristics of devices from their nominal values, producing the displacement of solution points from their nominal position. In this paper, a method to determine all the equilibrium regions in which real equilibrium points may fall is presented. The analysis is based on the introduction of the so‐called strip characteristics that represent the characteristics of devices affected by tolerances. They are modeled by polyhedral characteristics. Different situations may occur as tolerances grow. A nominal solution point may disappear, or on the other end, some solution point not present with nominal characteristics may appear. These possible events call for a classification of the equilibrium regions in either certain or uncertain, depending on the existence or not of an equilibrium point for any choice of real characteristics. The algorithm adopts linear programming techniques and a clustering algorithm. Copyright © 2015 John Wiley & Sons, Ltd.     

An efficient piecewise‐linear DC analysis method for general non‐linear circuits

The convergence problems of conventional DC analysis can be partly avoided by using piecewise‐linear analysis. This paper proposes a piecewise‐linear DC analysis method that can efficiently handle arbitrary couplings between non‐linear circuit elements. Piecewise‐linear modelling of the non‐linear circuit elements is automatically performed during simulation, using simplicial subdivisions. The number of linear regions, and thereby iterations, is considerably reduced by combining the common parts of separate simplicial subdivisions. Due to these reasons and since the method is formulated with the commonly used modified nodal approach, it has been possible to implement the method in the general‐purpose circuit simulator APLAC. The correct operation of the method is demonstrated with three examples. Copyright © 1999 John Wiley & Sons, Ltd.     

基于形态学广义分形维数的电力电子电路故障诊断

电力电子电路故障检测和诊断,是保证电力电子装置安全、可靠运行的一个重要手段.针对传统电力电子电路故障诊断方法存在的局限性,提出了一种基于数学形态学广义分形维数的新方法.结合分形几何理论,求取不同故障的输出电压波形的分形维数,以此作为故障特征,再与神经网络相结合,进行有效识别.以一个实际的Buck功率电路为例,对其各类故障信号进行了分析.结果表明,与传统的盒计数法计算的广义分形维数相比,形态学广义分形维数能够更加有效地区分Buck电路在不同状态下的信号,并且数学形态学只涉及简单的加减和取大、取小运算,因此计算简单快速,估计准确稳定,为准确判断电力电子电路故障诊断提供了一种快速有效的新方法.     

基于多目标线性规划的模拟电路软故障诊断方法

阐述了一种新的容差条件下基于多目标线性规划理论的模拟电路软故障诊断方法。通过灵敏度分析建立电路测试节点电压增量方程,并以元件参数变化量与标称值的百分比作为故障判据。采用多目标线性规划方法求解测试节点方程组来估算电路中各元件在一定故障情况下的参数变化百分比,将方程组的解与各元件容差范围相比较来定位故障元件。仿真结果表明,该方法兼顾故障元件的定位和故障元件参数变化量的估算,可以有效地实现模拟电路元件参数在一定容差范围内变化条件下的软故障诊断。     

基于双空间的融合特权信息支持向量机模拟电路故障诊断

针对模拟电路故障诊断识别率较低的问题,提出了基于双空间特征提取的融合特权信息支持向量机的模拟电路故障诊断新方法。首先对采集的信号进行主成分分析(principal component analysis,PCA)——特征提取;并用融合特权信息支持向量机LUPI-SVM(SVM of learning using privileged information,LUPI-SVM)分类器和SVM-GA分类器进行预分类;对分类结果不同的样本进行独立成分分析(independent component analysis,ICA)—特征提取,并用LUPI_SVM进行分类识别,Sallen-Key滤波电路故障诊断仿真实验结果表明该方法有效提高了分类的性能,为模拟电路故障诊断提供了新的途径。     

模拟电路统一软故障诊断的研究

在模拟电路故障诊断的诸多方法中,模拟电路统一软故障诊断方法成为新的研究热点。从模拟电路统一软故障诊断方法的提出,到模拟电路统一软故障诊断方法的改进,将其与基于多种方法融合的模拟电路软故障诊断方法做了比较。最后重点分析了模拟电路统一软故障诊断的研究现状和存在的不足,基于实用化的角度,从统一的模拟电路故障诊断的功能模块划分原则和方法、通用的模拟电路故障可诊断性分析方法、通用的模拟电路模块化分级诊断软故障诊断方法、统一的诊断效果评估指标4个方面指出了模拟电路统一软故障诊断的发展趋势。     

基于新型故障树的微控制器系统故障诊断方法

为更好解决以微控制器为主控芯片系统的故障诊断与故障搜寻问题,提出一种输入输出型的故障树模型,应用这种特殊故障树可简化故障推理机制,简便迅速的进行故障诊断与搜寻。该方法从故障树层间引出检测节点,并建立输入输出型最小割集故障树模型,实现了在某新型火炮上的快速自动化检测和精确的故障诊断与故障定位。     

基于BPNN的电力电子电路参数性故障诊断方法

提出了一种基于BP神经网络的电力电子电路参数性故障的在线诊断方法.通过研究电路中关键元器件的失效机理及电路整体性能的退化规律,选择输出电压基准变化率作为电路的故障特征参数,并确定故障阈值;利用BPNN对元器件参数及电路工作参数进行辨识,依据辨识结果获取电路故障特征参数,并将其与故障阈值比较,实现在线故障诊断.对典型Boost电路进行了仿真验证,结果表明该方法能够实时有效地实现电力电子电路的在线故障诊断.     

基于LS-SVM的电力电子电路故障预测方法

针对现有电力电子电路故障预测技术的不足,提出将电路特征性能参数和最小二乘支持向量机(least squares support vector machine,LS-SVM)预测算法结合,对电力电子电路进行故障预测.以Buck电路为例,选择电路输出电压作为监测信号,提取输出电压平均值及纹波值作为电路特征性能参数,并利用L...