基于知识图谱的装备故障诊断技术

传统的故障诊断方法为建立解析数学模型,该模型只能在装备发生故障后才能进行诊断分析,无法满足现在武器装备的故障检测需求。针对这一问题,文中以多层次知识图谱模型为基础,使用贝叶斯网络进行故障检测和诊断并完成建模,模型可以实现武器装备的状态变化检测及故障判断。实验结果表明,该模型可以通过状态的改变进而对故障类型进行判断。在对比实验中,文中所提算法模型的准确率与其他对比算法相比提高了2.5%、4.2%和5.6%,这说明该算法可以对装备进行故障诊断且综合性能良好。     

一种航天器异常检测案例关联方法

针对航天器异常检测系统中故障案例作用发挥不明显的问题,基于异常检测规则知识和故障案例,设计了一种关键词提取模式和全新的关联引擎,在航天器异常检测结果和故障案例之间建立了一种快速的关联机制,充分发挥了航天器异常检测系统中关联案例在故障识别、故障定位方面的作用。应用实例表明,该方法具有关联故障案例全面、数据处理运行高效的特点。     

基于自适应事件触发的跳变系统故障检测滤波

本文讨论了一类基于自适应事件触发机制的离散马尔科夫跳变系统在网络传输下的故障检测滤波器设计问题.对系统测量输出设计自适应事件触发机制，可以减少计算负载或节省有限的网络带宽.使用Bernoulli随机变量来描述网络是否能够成功地接收系统跳变模态，且基于Lyapunov稳定性理论设计了一种部分模态依赖的故障检测滤波器，使残差误差系统均方指数稳定且满足Η_∞性能指标，并通过求解线性矩阵不等式得到故障检测滤波器参数，通过仿真例子说明该设计方法的有效性.     

数字孪生增强的领域自适应航天器多余物检测

由于标注数据的短缺,对航天器多余物进行在线检测受到了较大的限制。文章研究了多余物的物理特性,在航天器的数字孪生系统中构建相应的多余物模型,提出了一种结合数字孪生技术增强的跨域自适应航天器多余物检测方法。该方法通过数字孪生技术获取航天器的实时数据,并借助于历史标注数据中的相似结构,以跨域自适应技术辅助实时在线推理的进行。设计了一种新型的跨域自适应模型,该模型采用共享网络结构以及门控机制,从而在复杂任务中更有效地挖掘先验知识,实现了跨域自适应技术与数字孪生技术的有机结合,以实现更高效、准确和实时的预测。此种方法可以全面地检测航天器各个部件的多余物状态。     

工业控制系统多传感器数据攻击检测方法研究

工业控制系统是国家健康有序发展的基石,当下网络攻击形式层出不穷,且随着两化的深度融合,工业控制系统面临着更加严峻的挑战。为了丰富相关研究,本文提出一种多传感器攻击方式,能够用近似正常的数据引起工控系统生产中断,且为了提高工控系统的安全性,提出一种基于过程稳定性的检测模型,通过结合结点数据之间的相关性特征,对异常数据进行放大,并投影到稳定状态的投影空间中,通过比较待检测数据投影矩阵和正常数据投影矩阵与形心之间的距离来判断异常情况。这种模型适用于全厂结点数据检测,并利用田纳西伊斯曼过程验证了模型的有效性。     

飞机操控系统故障诊断方法研究

为提高飞控系统的可靠性和安全性,用基于模型的状态估计故障诊断方法对飞机操控系统的故障检测和诊断隔离技术进行了研究。通过建立模型和构造残差利用线性多项式方法(Polynomial Method,PM)对故障进行诊断。对PM诊断方法进行了数学分析和论证,仿真结果表明PM方法不但对于故障信号比较敏感,并且对于干扰有较强的抑制能力,可保持较高的鲁棒性,提高故障检测效果,适用于飞控系统故障检测和隔离。     

基于新型故障搜寻策略的检测系统设计

为了达到复杂系统快速故障搜寻的目的,设计了一种基于二元决策图优化的新型故障搜寻策略的检测系统设计。通过对基于二元决策图优化的故障搜寻方法研究和实际的硬件电路设计,最终实现了检测系统的软硬件设计。使用这种方法能够很好的实现故障诊断系统在嵌入式平台的开发,并能够取得较好的诊断效果。     

基于模型的故障诊断在空间电源系统中的应用研究

空间电源系统工作时间长、运行环境特殊,在执行任务期间不可避免发生故障。为保障任务完成,需建立起空间电源系统在线故障诊断系统,实现在线故障检测、诊断和修复（FDIR）,防止故障传播和灾难性事故发生。在分析空间电源系统电路结构和故障特征基础上,建立起基于模型在线故障诊断系统。通过分析和论证,该诊断系统能够很好的诊断出空间电源系统电路的单点故障、多重故障及单传感器故障,并具有较好的诊断推理速度和较高的准确性。     

嵌入式系统中存储器性能研究

动态随机存储器是嵌入式系统的一个重要组成部分,而动态随机存储器故障是嵌入式系统故障的一个主要原因之一。在此从动态随机存储器的结构和失效模型出发,有针对地提出了用于检测性能的数据和读写方式,实验证明通过提出的检测方法能够有效地找出潜在的存储器故障,从而能够为嵌入式系统设计人员提供改善系统性能的方法和途径。     

物联网故障设备检测系统的设计与实现

物联网环境下的设备相对复杂,人工检测成本过高,故障检测误差较大,因此,设计并实现了一种基于物联网的故障设备检测系统。系统通过采集模块获取故障设备的实时参数,利用控制器为SIM900B的GPRS通信模块实现各模块间信息的传输,采用核心芯片为S7-200型PLC的检测诊断模块,对故障设备信息进行分析和处理,判断故障产生的原因和位置,实现对故障设备的实时管理和诊断。软件设计过程中,对基于物联网故障设备检测系统的流程进行了详细分析,并给出无线传感节点接收和处理故障设备数据的程序代码。实验结果表明,所提系统具有很高的可行性及实用性。     

System reliability analysis of an N-version programming application

This paper presents a quantitative reliability analysis of a system designed to tolerate both hardware and software faults. The system achieves integrated fault tolerance by implementing N-version programming (NVP) on redundant hardware. The system analysis considers unrelated software faults, related software faults, transient hardware faults, permanent hardware faults, and imperfect coverage. The overall model is Markov in which the states of the Markov chain represent the long-term evolution of the system-structure. For each operational configuration, a fault-tree model captures the effects of software faults and transient hardware faults on the task computation. The software fault model is parameterized using experimental data associated with a recent implementation of an NVP system using the current design paradigm. The hardware model is parameterized by considering typical failure rates associated with hardware faults and coverage parameters. The authors results show that it is important to consider both hardware and software faults in the reliability analysis of an NVP system, since these estimates vary with time. Moreover, the function for error detection and recovery is extremely important to fault-tolerant software. Several orders of magnitude reduction in system unreliability can be observed if this function is provided promptly     

Test for detection and location of intermittent faults incombinational circuits

Faults in combinational circuits are either permanent or intermittent. Intermittent faults tend to be environment-dependent; hence altering the environment might rectify these faults. These faults can be detected by applying random input-vectors (IV). The existence of random intermittent faults might require applying more random IV before detection. The detection of permanent faults requires fewer random IV but correction demands location and replacement of the faulty device, if repair is not feasible. Thus correction of a permanent fault costs more than that of an intermittent fault. The correction cost can be reduced by detecting the type of fault. Since most operational failures in a circuit are due to intermittent faults, it is very important to detect the type of fault in order to find a cheaper solution. This paper discusses the behavior of permanent and intermittent faults in combinational circuits, and introduces a test-detection model (TDM) for these faults. The error latency for an intermittent fault is derived. Two test-strategies are intermixed in the model: random testing for fault-detection, and deterministic testing for deciding on the type of fault. The activity of intermittent faults that requires the minimum number of IV for detection is emphasized. Simulation is used to demonstrate the validity of TDM. Although the variables required in TDM can be difficult to evaluate, estimation of their values is not impossible. A worst-case analysis can always be adopted, where variables are easily evaluated, to find an upper bound on the error latency; thus detection of an intermittent fault is assured with a very high probability. The cost-saving offered by intermittent-fault corrections shows the practical aspect of TDM     

基于特征结构配置的飞控系统故障检测与诊断

针对具有未知扰动输入的飞行控制系统,运用特征值配置设计了一种用于故障检测和诊断的观测器,他通过对观测器进行左特征向量的配置使得残差与干扰分布方向正交,故障检验残差r与未知输入干扰d之间的传递函数阵为零,从而使残差与干扰直接解耦.通过这种方法,残差信号得以对干扰具有鲁棒性,使FDI算法不受系统不确定性干扰的影响,提高系统故障诊断的可靠性和精度.同时通过残差信号估计故障,能在线辨识故障的形态,仿真结果验证了该方法的有效性.     

Application of the hierarchical fault model to reliability considerations

The present paper uses the hierarchical fault model. By this it is possible to consider fault propagation in a system based on the layer model. Hardware faults as well as software faults can be described with the same model. Finally, human errors are considered.     

模拟电路故障诊断的PSpice与Matlab仿真分析研究

根据模拟电路故障诊断中的测前模拟诊断SBT法,本文采用PSpice对待测电路CUT故障进行模拟仿真,通过小波包分析和信息熵方法提取故障电路输出信号的特征向量,利用Matlab设计的神经网络算法构建故障分类器并对电路故障进行识别与诊断。仿真实验结果表明将PSpice与Matlab相结合的诊断方法能够有效地诊断模拟电路故障,为模拟电路故障诊断的教学和科研提供参考。     

Multiresolution Abnormal Trace Detection Using Varied-Length n-Grams and Automata

Detection and diagnosis of faults in a large-scale distributed system is a formidable task. Interest in monitoring and using traces of user requests for fault detection has been on the rise recently. In this paper we propose novel fault detection methods based on abnormal trace detection. One essential problem is how to represent the large amount of training trace data compactly as an oracle. Our key contribution is the novel use of varied-length n-grams and automata to characterize normal traces. A new trace is compared against the learned automata to determine whether it is abnormal. We develop algorithms to automatically extract n-grams and construct multiresolution automata from training data. Further, both deterministic and multihypothesis algorithms are proposed for detection. We inspect the trace constraints of real application software and verify the existence of long n-grams. Our approach is tested in a real system with injected faults and achieves good results in experiments     

Software Reliability Analysis by Considering Fault Dependency and Debugging Time Lag

Over the past 30 years, many software reliability growth models (SRGM) have been proposed. Often, it is assumed that detected faults are immediately corrected when mathematical models are developed. This assumption may not be realistic in practice because the time to remove a detected fault depends on the complexity of the fault, the skill and experience of personnel, the size of debugging team, the technique(s) being used, and so on. During software testing, practical experiences show that mutually independent faults can be directly detected and removed, but mutually dependent faults can be removed iff the leading faults have been removed. That is, dependent faults may not be immediately removed, and the fault removal process lags behind the fault detection process. In this paper, we will first give a review of fault detection & correction processes in software reliability modeling. We will then illustrate the fact that detected faults cannot be immediately corrected with several examples. We also discuss the software fault dependency in detail, and study how to incorporate both fault dependency and debugging time lag into software reliability modeling. The proposed models are fairly general models that cover a variety of known SRGM under different conditions. Numerical examples are presented, and the results show that the proposed framework to incorporate both fault dependency and debugging time lag for SRGM has a better prediction capability. In addition, an optimal software release policy for the proposed models, based on cost-reliability criterion, is proposed. The main purpose is to minimize the cost of software development when a desired reliability objective is given.     

基于粗糙集理论的梭式窑故障诊断专家系统

针对梭式窑运行故障多且难以快速检测和定位的问题,研究并设计出一种基于粗糙集理论的故障诊断专家系统。详细分析了专家系统粗糙集理论的信息表示、知识约简及诊断概率模型,重点设计并介绍了专家诊断系统中各个部分的详细组成,最后还给出了本系统的实际开发与实验情况。运行实践表明,该专家系统的知识模型适应性好,推理结果可靠稳定,具有较好的应用和推广价值。     

Performance analysis and fault tolerance of randomized routing on Clos networks

Beside universality and very low latency, Youssef's randomized self-routing algorithms [25] have high tolerance for multiple faults and more strikingly have the potential for fault tolerance without diagnosis. In this paper we study the performance of Youssef's routing algorithms for faulty Clos networks in the presence of multiple faults in multiple columns with and without fault detection. We show that with fault detection and diagnosis, randomized routing algorithms provide scalable, very efficient and fault tolerant routing mechanisms. Without fault detection and diagnosis, randomized routing provides good fault tolerance for faulty switches in either the first or the second column. The delays become large for faults in the third column or for faults in more than one column. In conclusion, randomized routing enables the system to run without periodic fault detection/diagnosis, and if and when the performance degrades beyond a certain threshold, diagnosis can be performed to improve the routing performance. This revised version was published online in June 2006 with corrections to the Cover Date.     

Multifault diagnosis in WSN using a hybrid metaheuristic trained neural network

Wireless sensor networks are susceptible to failures of nodes and links due to various physical or computational reasons. Some physical reasons include a very high temperature, a heavy load over a node, and heavy rain. Computational reasons could be a third-party intrusive attack, communication conflicts, or congestion. Automated fault diagnosis has been a well-studied problem in the research community. In this paper, we present an automated fault diagnosis model that can diagnose multiple types of faults in the category of hard faults and soft faults. Our proposed model implements a feed-forward neural network trained with a hybrid metaheuristic algorithm that combines the principles of exploration and exploitation of the search space. The proposed methodology consists of different phases, such as a clustering phase, a fault detection and classification phase, and a decision and diagnosis phase. The implemented methodology can diagnose composite faults, such as hard permanent, soft permanent, intermittent, and transient faults for sensor nodes as well as for links. The proposed implementation can also classify different types of faulty behavior for both sensor nodes and links in the network. We present the obtained theoretical results and computational complexity of the implemented model for this particular study on automated fault diagnosis. The performance of the model is evaluated using simulations and experiments conducted using indoor and outdoor testbeds.