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文中介绍了模拟电路故障诊断的研究现状。主要对基于神经网络的模拟电路故障诊断方法进行了简要阐述,并预测了诊断方法的研究热点和发展趋势。 相似文献
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随着电子信息技术的发展,现在已经进入到了电子时代,电路的故障诊断越来越重要,本文在模拟电路故障特征和种类的基础上,简要的分析了模拟电路故障诊断的神经网络法和支持向量机法,结合模拟电路的实际情况,结合支持向量机法,对模拟电路故障诊断方法进行了设计,并阐述了虚拟维修过程。 相似文献
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分析了在模拟电路故障诊断过程中所采用的几种常用诊断方法，以及未来的发展趋势，并且介绍了模拟电路故障诊断的小波神经网络方法。 相似文献
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介绍了模拟电路故障诊断研究的必要性、发展现状和研究难点。对该技术进行了概述,列出了其优缺点和适用范围,最后讨论了该技术的发展趋势。 相似文献
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本文采用分数阶傅立叶变换用于模拟电路的故障诊断中,用分数阶傅立叶变换对电路采样数据做预处理,然后进行PCA降维,结合神经网路进行故障诊断.实验结果表明,该方法取得了良好的诊断结果. 相似文献
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现代伺服系统规模庞大,结构复杂,且通常工作环境恶劣,故障发生率高,故障诊断费时费力。为了提高伺服系统故障诊断定位效率,基于故障树分析和虚拟仪器技术相结合在LabView软件平台上开发了伺服故障诊断定位系统。设计了一种基于最小割集表示的等价故障树的,结合模拟退火粒子群算法对神经网络的训练进行优化,使其故障诊断定位响应时间和准确度都显著提高。最后实验证明所设计系统采用的分析算法能够快速准确的进行故障诊断定位,对故障诊断定位技术的发展具有一定的参考和实际意义。 相似文献
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针对飞机温控系统的故障复杂性,提出了一种基于功能的以模糊Petri网为推理算法的故障诊断方法。首先根据系统分析,推导出子系统和系统功能参数,建立了描述功能层次关系的功能模型,提高了故障诊断的直观性和有效性;然后利用模糊Petri网的快速和并行推理能力,建立了反映功能模型的故障诊断模型,定位故障功能组件,提高了诊断的快速性和精确性;最后通过实例验证了该方法的有效性。 相似文献
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针对机载航空相机补偿板自身特性所造成的故障诊断繁琐、费事、效率低等实际l『口]题,采用蚁群策略,设计出航空相机补偿板故障诊断系统;参考所建立的补偿板故障树模型,确定补偿板的最优故障诊断次序,设计了故障诊断系统的软硬件,理论分析与实践检测结果均表明所设计补偿板故障诊断系统具有快速、可靠的特点,适用于其他航空电子设备系统的故障诊断类问题的解决。 相似文献
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将量子神经网络(QNN)方法应用到电网故障中,建立故障诊断模型。首先以保护装置和断路器的动作信息为条件属性集,建立电网故障决策表,然后将简化后的决策表作为训练样本,训练量子神经网络,使网络具有故障诊断功能。仿真实验结果表明,提出的算法有效提高了故障诊断的正确性和效率。 相似文献
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《Journal of The Franklin Institute》2022,359(8):3979-3999
This paper addresses an active fault diagnosis problem for a class of discrete-time closed-loop system with stochastic noise. By introducing the theories of system identification, a novel active fault diagnosis method is developed to detect and isolate the faults. An important advantage of the proposed method is that there is no need to cut off the original input signal, which is necessary in most active fault diagnosis methods. Firstly, due to the features of the faults, we transform the problem of fault diagnosis into a problem of model selection by estimating model parameters. Then, the sufficient condition for active fault diagnosability is analysed, and the property that auxiliary input signal can enhance the fault diagnosability is given. Finally, simulation studies are carried out to demonstrate the effectiveness and applicability of the proposed method. 相似文献
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The purpose of fault diagnosis of stochastic distribution control (SDC) systems is to use the measured input and the system output probability density functions (PDFs) to obtain the fault information of the SDC system. When the target PDF is known, the purpose of fault tolerant control of stochastic distribution control system is to make the output PDF still track the given distribution using the fault tolerant controller. However, in practice, time delay may exist in the data (or image) processing, the modeling and transmission phases. When time delay is not considered, the effectiveness of the fault detection, diagnosis and fault tolerant control of stochastic distribution systems will be reduced. In this paper, the rational square-root B-spline is used to approach the output probability density function. In order to diagnose the fault in the dynamic part of such systems, it is then followed by the novel design of a nonlinear neural network observer-based fault diagnosis algorithm. The time delay term will be deleted in the stability proof of the observation error dynamic system. Based on the fault diagnosis information, a new fault tolerant controller based on PI tracking control is designed to make the post-fault probability density function still track the given distribution, which is dependent of the time delay term. Finally, simulations for the particle distribution control problem are given to show the effectiveness of the proposed approach. 相似文献