设计高阶PI观测器对线性系统故障作鲁棒检测

针对具有干扰的线性定常系统,研究了基于高阶PI观测器的鲁棒故障检测设计问题.基于Sylvester矩阵方程的参数化解,给出了干扰与残差解耦的充要条件,并提出了基于高阶PI观测器的线性系统鲁棒故障检测参数化设计方法.数值算例及仿真分析表明所提鲁棒故障检测参数化设计方法是有效的.     

Fault detection based on one-class deep learning for manufacturing applications limited to an imbalanced database

Despite extensive studies for the industrial applications of deep learning, its actual usage in manufacturing sites has been extremely restrained by the difficulty in obtaining sufficient industrial data, especially for production failure cases. In this study, we introduced a fault-detection module based on one-class deep learning for imbalanced industrial time-series data, which consists of three submodules, namely, time-series prediction based on deep learning, residual calculation, and one-class classification using one-class support vector machine and isolation forest. Four different networks were used for the time-series prediction: multilayer perception (MLP), residual network (ResNet), long–short-term memory (LSTM), and ResNet–LSTM, each trained with the one-class data having only the production success cases. We adopted the residuals of the deep-learning prediction as an elaborated feature for the construction of the one-class classification. We also tested the fault-detection module with the actual mass production data of a die-casting process. By adopting the features elaborated by the deep-learning time-series prediction, we showed that the total accuracy of the one-class classification significantly improved from 90.0% to 96.0%. Especially for its capability to detect production failures, the accuracy improved from 84.0% to 96.0%. The area under the receiver operating characteristics (AUROC) also improved from 87.56% to 98.96%. ResNet showed the best performance for detecting production failures, whereas ResNet–LSTM produced better results for ensuring the production success. Our results suggest that the one-class deep learning is a promising approach for extracting important features from time-series data to realize a one-class fault-detection module.     

An observer and signal-processing approach to FDI for the industrial actuator benchmark test

In order to apply the best fault-detection and diagnosis scheme, it is required to investigate the process model profoundly and the kinds of faults to be detected. Especially, the process excitation and the effect of the fault being considered play an important role. This is the starting point for the choice of one of the various model-based fault-detection methods. According to this strategy, two different approaches, an observer-based and a signal-based approach, are selected for the two given faults of the benchmark task. It is shown that the use of adaptive thresholds can significantly improve the performance of the fault-detection scheme with respect to the false alarm rate and the delay in detection.     

Fault Detection for Uncertain Fuzzy Systems: An LMI Approach

This paper studies the problem of designing a robust fault-detection system for uncertain Takagi-Sugeno fuzzy models. The worst case fault sensitivity measure is formulated in terms of linear matrix inequalities. The existence of a robust fault detection system that guarantees i) the L₂-gain from a fault signal to a residual signal greater than a prescribed value and ii) the L₂-gain from an exogenous input to a residual signal less than a prescribed value is given in terms of the solvability of linear matrix inequalities. Numerical examples are used to illustrate the effectiveness of the proposed design techniques.     

一种基于LMI的鲁棒故障诊断滤波器设计

研究了一类含有扰动的线性系统鲁棒故障诊断滤波器设计问题. 文中引入一种能同时体现残差对扰动信号鲁棒性和对故障信号灵敏性的性能指标, 利用H_∞理论把求解滤波器的问题转化为H_∞优化设计问题. 应用线性矩阵不等式(LMI)技术, 对此性能指标进行优化, 给出并证明了该设计问题解的存在性条件和滤波器增益阵的求解方法, 最后, 通过仿真实例验证了方法的有效性.     

一种基于小波分析的故障检测与诊断

小波分析是一种时变信号时-频两维分析方法.根据小波分析的思想,构造出一种新型机械设备故障诊断装置,使得机械故障的诊断结果更加准确,并在实际应用中取得了良好效果.实践证明这种拟小波理论的信号处理方法在故障诊断中是十分有效的.     

PVM环境下实时检错机制的研究与实现

PVM（Parallel Virtual Machine）作为一种主流的集群并行计算环境，能够应付主机和网络故障并且提供轮询机制和故障通知原语来建立容错应用。由于PVM原有的故障检测机制不能满足实时性要求，因此提出并实现了两种改进PVM检错机制实时性能的方法，使得对主机故障事件的发现时间缩短了一万倍以上。     

On the value of static analysis for fault detection in software

No single software fault-detection technique is capable of addressing all fault-detection concerns. Similarly to software reviews and testing, static analysis tools (or automated static analysis) can be used to remove defects prior to release of a software product. To determine to what extent automated static analysis can help in the economic production of a high-quality product, we have analyzed static analysis faults and test and customer-reported failures for three large-scale industrial software systems developed at Nortel Networks. The data indicate that automated static analysis is an affordable means of software fault detection. Using the orthogonal defect classification scheme, we found that automated static analysis is effective at identifying assignment and checking faults, allowing the later software production phases to focus on more complex, functional, and algorithmic faults. A majority of the defects found by automated static analysis appear to be produced by a few key types of programmer errors and some of these types have the potential to cause security vulnerabilities. Statistical analysis results indicate the number of automated static analysis faults can be effective for identifying problem modules. Our results indicate static analysis tools are complementary to other fault-detection techniques for the economic production of a high-quality software product.     

交通信号灯故障检测系统设计与实现

针对现有信号灯故障检测装置功能不足且结构复杂的问题,设计了一种基于单片机和GPRS网络的交通信号灯故障检测系统.该系统采用巡回检测和电容充放电的方法采集信号机输出端的电压和电流信息,对信息进行逻辑运算以分析信号灯和信号机的故障,并建立了电容充电时间数学模型,分析充电时间与信号机输出端负载功率的关系,避免使用A/D功率采集电路,简化了电路结构.本系统已作为样机应用于山东省龙口市,应用结果表明系统能有效检测信号机和信号灯的常见故障.     

一种改进PVM检错机制实时性能的方法

PVM的设计目标是连接一个异构的计算机和网络的集合，给用户提供一个并行计算平台来运行他们的MPP或集群计算应用。运行在集群上的应用经常碰到诸如网络故障、主机故障和进程故障等各种异常故障，可靠性是这类平台面临的主要问题。PVM能够应付主机和网络故障并且提供轮询机制和故障通知原语来建立容错应用。由于在设计PVM时对在异构环境下软件的适用性投入了太多的考虑，PVM原有的故障检测机制不能满足实时性的要求。为了解决这个问题，我们提出并实现了一种改进PVM检错机制实时性能的方法，使得对主机故障事件的发现时间缩短了五千多倍。     

考虑用户行为和排错延迟的软件运行可靠性增长模型

传统的软件可靠性模型大多都假设软件测试环境和运行环境相同,也就是使用软件测试阶段的失效数据来预测软件运行可靠性。众所周知,软件固有故障的排除能提高系统可靠性,然而另一种现象就是随着用户对软件熟悉程度的提高,软件的失效率也会降低。文中研究了软件固有故障检测过程、固有故障纠正过程和外在失效过程的特征,建立了考虑用户行为和排错延迟下的软件运行可靠性增长模型。通过一组来自于开源软件用户缺陷跟踪系统中的真实数据进行数值分析,实验结果表明提出的模型具有较好的效果。     

Software reliability assessment tool based on object-oriented analysis and its application

In general, the software testing-efforts which are spent in large-scale software development account for a half of the total amount of the development effort. Therefore, the management of fault-detection and fault-correction activities in the testing phase is very important to efficiently and economically develop a highly-reliable software product. In this paper, a software management tool which aids the quality/reliability assessment and testing-progress control in the testing phase is developed. This tool consists of several sub-systems that analyze software fault-detection data and assess software quality/reliability and testing-progress based on adopted software reliability growth models. Also, we use JAVA language to implement the tool. The JAVA language is widely known as an object-oriented and platform-free programming language. These characteristics are suitable for constructing our tool, because the tool will be revised to adopt new software reliability growth models and/or new testing-control techniques. This revised version was published online in June 2006 with corrections to the Cover Date.     

An empirical evaluation of P system testing techniques

This paper presents the existing techniques for P system testing and performs an empirical evaluation of their fault-detection efficiency. The comparison is performed using mutation testing and, based on the results obtained, some improved testing methodologies are proposed.     

A representation for coordination fault detection in large-scale multi-agent systems

Teamwork requires that team members coordinate their actions. The representation of the coordination is a key requirement since it influences the complexity and flexibility of reasoning team-members. One aspect of this requirement is detecting coordination faults as a result of intermittent failures of sensors, communication failures, etc. Detection of such faults, based on observations of the behavior of agents, is of prime importance. Though different solutions have been presented thus far, none has presented a comprehensive and efficient resolution for large-scale teams. This paper presents a formal approach to representing multi-agent coordination, and multi-agent observations, using matrix structures. This representation facilitates easy representation of coordination requirements, modularity, flexibility and reuse of existing systems. Based on this representation, we present a novel solution for fault-detection that is both generic and efficient for large-scale teams. We demonstrate the modularity of the representation by presenting a reuse of existing systems and by importing other models (e.g. hierarchical systems) into the new representation. Finally, we extend the representation to support dynamical aspects of complex systems.     

Mirror adaptive random testing

Recently, adaptive random testing (ART) has been introduced to improve the fault-detection effectiveness of random testing for non-point types of failure patterns. However, ART requires additional computations to ensure an even spread of test cases, which may render ART less cost-effective than random testing. This paper presents a new technique, namely mirror ART, to reduce these computations. It is an integration of the technique of mirroring and ART. Our simulation results clearly show that mirror ART does improve the cost-effectiveness of ART.     

Fault-tolerant control based on algebraic derivative estimation applied on a magnetically supported plate

A fault-tolerant control method based on algebraic derivative estimation is introduced. It is applied on an electromagnetically supported plate as an example of a nonlinear and an open-loop unstable system. The design of the closed loop control is facilitated assuming that relevant faults are identified sufficiently precisely and fast. This is justified by a novel robust model-based fault identification scheme which relies on algebraic methods for numerical differentiation. Derivative estimation parameters and fault-detection thresholds are chosen systematically based on the properties of the measurements. The experimental results show the practical usefulness of the presented methods.     

基于CompactPCI技术的双冗余网卡设计

本文介绍了一种基于CompactPCI技术的双冗余网卡的硬件和驱动软件设计。本设计从硬件和软件上完全满足高可靠设备的需求,网卡切换时间小于6毫秒;软件驱动具有判错和自动切换功能,在设计上有独到之处。该设计已应用在某高可靠设备上。     

Necessary and sufficient conditions for componentwise stability of interval matrix systems

In the asymptotic stability (AS) analysis of interval matrix systems, some results are available that operate only as sufficient conditions, based on a unique test matrix, adequately built from the interval matrix. Our note reveals the complete role of this test matrix for fully characterizing the componentwise asymptotic stability (CWAS) of interval matrix systems. CWAS is a special type of AS which ensures the flow invariance of certain time-dependent sets with respect to the state-space trajectories. Hence, the sufficient conditions for AS get a new and deeper meaning by their reformulation as necessary and sufficient conditions with respect to the stronger property of CWAS.     

网格检查点恢复服务及其应用编程接口分析

检查点机制作为一种软件容错机制，可以与新出现的广域分布式系统网格相结合，更好地满足网格系统的容错要求。文中详细分析了检查点回卷恢复协议的关键点，并对数据网格中GridCPR API进行了解析，提出一些改进，这样就更有利于网格系统的故障检测和容错服务。     

Test suite oscillations

This paper proposes a set of new software test-diversity measures based on control oscillations of test suites. Oscillation Diversity uses conversion, inversion, and phase transformation to vary test suite amplitudes, frequencies, and phases. Resistance and inductance are defined as measures of diversification difficulty. The experimental results show correlation between some Oscillation Diversity measures and fault-detection effectiveness.