模拟电路故障诊断可信度研究

提出了描述标称转移矩阵Ｚ０的各标征向量几何分布性状的Ｖｏｒｏｎｏｉ多胞体，定义了描述测量向量ｄＵ在标征向量Ｚｉ中位置的标征干扰角θｕｉ。然后利用这两个概念揭示了容差─故障电路可诊充要和充分条件，讨论了定位故障的极值法和阈值法的有效性、局限性，及提高定位准确率的可能途径。     

Diagnosability of discrete event systems subject to permanent sensor failures

This paper considers a failure diagnosis problem for discrete event systems subject to permanent sensor failures. A notion of diagnosability subject to permanent sensor failures is introduced with respect to a certain nondeterministic observation mask. For its verification, an aggregated Mealy automaton with a deterministic and state-dependent observation mask is defined. It is shown that the diagnosability of the aggregated Mealy automaton is equivalent to the diagnosability of the original system subject to permanent sensor failures. Then, a method for verifying the diagnosability of the aggregated Mealy automaton is presented. Moreover, the delay bound within which the occurrence of any failure string can be detected subject to permanent sensor failures is computed.     

Detection,isolation and diagnosability analysis of intermittent faults in stochastic systems

Intermittent faults (IFs) have the properties of unpredictability, non-determinacy, inconsistency and repeatability, switching systems between faulty and healthy status. In this paper, the fault detection and isolation (FDI) problem of IFs in a class of linear stochastic systems is investigated. For the detection and isolation of IFs, it includes: (1) to detect all the appearing time and the disappearing time of an IF; (2) to detect each appearing (disappearing) time of the IF before the subsequent disappearing (appearing) time; (3) to determine where the IFs happen. Based on the outputs of the observers we designed, a novel set of residuals is constructed by using the sliding-time window technique, and two hypothesis tests are proposed to detect all the appearing time and disappearing time of IFs. The isolation problem of IFs is also considered. Furthermore, within a statistical framework, the definition of the diagnosability of IFs is proposed, and a sufficient condition is brought forward for the diagnosability of IFs. Quantitative performance analysis results for the false alarm rate and missing detection rate are discussed, and the influences of some key parameters of the proposed scheme on performance indices such as the false alarm rate and missing detection rate are analysed rigorously. The effectiveness of the proposed scheme is illustrated via a simulation example of an unmanned helicopter longitudinal control system.     

The pessimistic diagnosability of alternating group graphs under the PMC model

The process of identifying faulty processors is called the diagnosis of the system. Several diagnostic models have been proposed, the most popular is the PMC (Preparata, Metze and Chen) diagnostic model. The pessimistic diagnosis strategy is a classic strategy based on the PMC model in which isolates all faulty nodes within a set containing at most one fault-free node. A system is t/t$t/t$-diagnosable if, provided the number of faulty processors is bounded by t, all faulty processors can be isolated within a set of size at most t with at most one fault-free node mistaken as a faulty one. The pessimistic diagnosability of a system G  , denoted by _tp(G)$t_p(G)$, is the maximal number of faulty processors so that the system G   is t/t$t/t$-diagnosable. Jwo et al. [11] introduced the alternating group graph as an interconnection network topology for computing systems. The proposed graph has many advantages over hypercubes and star graphs. For example, for all alternating group graphs, every pair of vertices in the graph are connected by a Hamiltonian path and the graph can embed cycles with arbitrary length with dilation 1. In this article, we completely determine the pessimistic diagnosability of an n  -dimensional alternating group graph, denoted by _AGn${\mathit{AG}}_n$. Furthermore, _tp(_AGn)=4n−11$t_p({\mathit{AG}}_n)=4n-11$ for n≥4$n\ge 4$.     

A Low-Cost Fault-Tolerant Structure for the Hypercube

We propose a new, low-cost fault-tolerant structure for the hypercube that employs spare processors and extra links. The target of the proposed structure is to fully tolerate the first faulty node, no matter where it occurs, and almost fully tolerate the second, meaning that the underlying hypercube topology can be resumed if the second faulty node occurs at most locations—expectantly 92% of locations. The unique features of our structure are that (1) it utilizes the unused extra link-ports in the processor nodes of the hypercube to obtain the proposed topology, so that minimum extra hardware is needed in constructing the fault-tolerant structure and (2) the structure's node-degrees are low as desired—the primary and spare nodes all have node-degrees of n + 2 for an n-dimensional hypercube. The number of spare nodes is one fourth of primary nodes. The reconfiguration algorithm in the presence of faults is elegant and efficient. The proposed structure also effectively enhances the diagnosability of the hypercube system. It is shown that the diagnosability of the structure is increased to n + 2, whereas an ordinary n-dimensional hypercube has diagnosability n.     

Diagnosability of fuzzy discrete event systems

In this paper, discrete event systems (DESs) are reformulated as fuzzy discrete event systems (FDESs) and fuzzy discrete event dynamical systems (FDEDSs). These frameworks include fuzzy states, events and IF-THEN rules. In these frameworks, all events occur at the same time with different membership degrees. Fuzzy states and events have been introduced to describe uncertainties that occur often in practical problems, such as fault diagnosis applications. To measure a diagnoser’s fault discrimination ability, a fuzzy diagnosability degree is proposed. If the diagnosability of the degree of the system yields one a diagnoser can be implemented to identify all possible fault types related to a system. For any degree less than one, researchers should not devote their time to distinguish all possible fault types correctly. Thus, two different diagnosability definitions FDEDS and FDES are introduced. Due to the specialized fuzzy rule-base embedded in the FDEDS, it is capable of representing a class of non-linear dynamic system. Computationally speaking, the framework of diagnosability of the FDEDS is structurally similar to the framework of diagnosability of a non-linear system. The crisp DES diagnosability has been turned into the term fuzzy diagnosability for the FDES. The newly proposed diagnosability definition allows us to define a degree of diagnosability in a class of non-linear systems. In addition, a simple fuzzy diagnosability checking method is introduced and some numerical examples are provided to illustrate this theoretical development. Finally, the potential applications of the proposed method are discussed.     

面向可重组制造系统的快速诊断技术研究

在分析现有质量控制技术的基础上,提出了面向可重组制造系统故障诊断的架构和一种基于粗糙集故障诊断的方法。该方法利用传统统计过程控制数据,并结合现场传感器数据作为数据源,以粗糙集为知识获取工具进行数据处理,得到最小规则集,最终得到故障诊断结果。以一个实例验证了设计方案的有效性。     

多工位装配过程中测量方案的研究

为保证产品质量并适应企业信息化发展的需要,对多工位装配过程中测量方案的优化问题进行了研究.文中基于状态空间方程建立了多工位装配过程中的误差传递模型,用以反映过程中不同工位上的误差信息和测量信息,并提出了诊断能力的概念来度量该测量方案的执行能力,在上述基础上得到一种优化方法来构建具有完全诊断能力的优化测量方案.最后,以一个三工位薄壁件装配过程为例进行了说明和验证.