设备状态监测与诊断系统的概念模型

采用任何软件技术实现的设备状态监测与故障诊断系统都应该遵循同一个高层次抽象的概念模型,采用统一建模语言,以基于Web的设备远程监测与诊断系统（WRMFDS）的概念模型为实例,建立该领域的概念模型,采用面向对象分析和设计模式建立相应的关键对象模型。设计和实现的WRMFDS原型系统在一定程度上证明了该概念模型的正确性与有效性。     

Artificial intelligence for monitoring and supervisory control of process systems

Complex processes involve many process variables, and operators faced with the tasks of monitoring, control, and diagnosis of these processes often find it difficult to effectively monitor the process data, analyse current states, detect and diagnose process anomalies, or take appropriate actions to control the processes. The complexity can be rendered more manageable provided important underlying trends or events can be identified based on the operational data (Rengaswamy and Venkatasubramanian, 1992. An Integrated Framework for Process Monitoring, Diagnosis, and Control Using Knowledge-based Systems and Neural Networks. IFAC, Delaware, USA, pp. 49–54.). To assist plant operators, decision support systems that incorporate artificial intelligence (AI) and non-AI technologies have been adopted for the tasks of monitoring, control, and diagnosis. The support systems can be implemented based on the data-driven, analytical, and knowledge-based approach (Chiang et al., 2001. Fault Detection and Diagnosis in Industrial Systems. Springer, London, Great Britain). This paper presents a literature survey on intelligent systems for monitoring, control, and diagnosis of process systems. The main objectives of the survey are first, to introduce the data-driven, analytical, and knowledge-based approaches for developing solutions in intelligent support systems, and secondly, to present research efforts of four research groups that have done extensive work in integrating the three solutions approaches in building intelligent systems for monitoring, control and diagnosis. The four main research groups include the Laboratory of Intelligent Systems in Process Engineering (LISPE) at Massachusetts Institute of Technology, the Laboratory for Intelligent Process Systems (LIPS) at Purdue University, the Intelligent Engineering Laboratory (IEL) at the University of Alberta, and the Department of Chemical Engineering at University of Leeds. The paper also gives some comparison of the integrated approaches, and suggests their strengths and weaknesses.     

DCOM在设备远程监测与故障诊断系统中的应用

讨论了基于DCOM的设备远程监测与故障诊断系统的技术特点,给出了利用DCOM技术实现分布式功能的设备远程监测与故障诊断系统体系结构及其运行机制,并提出了适合于远程在线监测的瘦Web客户端构架模式,给出了一种详细的实现方案,并在实际项目中验证了该模型的有效性。     

神经网络ART模型在故障诊断中的应用

讨论了目前最成功的一种无导师神经网络模型──自适应谐振理论ＡＲＴ。分析了ＡＲＴ的工作原理，给出了ＡＲＴ的具体算法（已在ＰＣ－４８６上用Ｃ语言实现）；指出了ＡＲＴ的实质，并以“有轨自动物料搬运小车系统”为例详述了ＡＲＴ在故障诊断中的工作过程，获得了很好的结果。     

Expert systems and database systems: how can they serve each other?

Abstract Expert systems are becoming increasingly complex and diverse. The need for efficient data management for their growing knowledge bases is apparent. Moreover, with the widespread use of Database Management Systems, the operational data required by the expert system is often already available from an online database. Hence the interaction of expert systems and databases is a topic which is receiving increasing attention. This paper reviews existing techniques for such interaction and describes a novel dictionary–driven approach to the problem, called a Dictionary Interface for Expert Systems and Databases (Difead). A prototype of Difead is described, which couples a Medical Diagnosis System, written in Lisp, with a relational database.     

Analysis of Secure Mobile Grid Systems: A systematic approach

Developing software through systematic processes is becoming more and more important due to the growing complexity of software development. It is important that the development process used integrates security aspects from the first stages at the same level as other functional and non-functional requirements. Systems which are based on Grid Computing are a kind of systems that have clear differentiating features in which security is a highly important aspect. The Mobile Grid, which is relevant to both Grid and Mobile Computing, is a full inheritor of the Grid with the additional feature that it supports mobile users and resources. A development methodology for Secure Mobile Grid Systems is proposed in which the security aspects are considered from the first stages of the life-cycle and in which the mobile Grid technological environment is always present in each activity. This paper presents the analysis activity, in which the requirements (focusing on the grid, mobile and security requirements) of the system are specified and which is driven by reusable use cases through which the requirements and needs of these systems can be defined. These use cases have been defined through a UML-extension for security use cases and Grid use cases which capture the behaviour of this kind of systems. The analysis activity has been applied to a real case.     

一种新的网络故障检测方法

文章提出了一种基于粗糙集和径向基函数思想的网络层故障检测算法——RSMNBP。这种新的方法提供网络层状态数据的采集、分析、存储和响应功能,具有简化样本、适应性强、容错性高等特点,能有效处理网络层故障诊断中噪声和不相容的信息。由于检测问题的实质是一种映射,该方法用一种前馈型网络来逼近这种映射关系,实现对故障的有效分类。同时,RSMNBP的网络结构可以随着网络层中各种服务和应用的变化而构造。仿真表明,利用该方法实现的系统与同类的其他方法相比,提高了检测准确率和诊断速度。     

A distributed adaptable software architecture derived from a component model

Today, Information Systems (IS) are often distributed and heterogeneous. Thus, software systems become more and more complex and their evolution is difficult to manage. Our works deal with engineering of heterogeneous distributed systems based on reuse. Such systems need a distributed adaptable software architecture to be implemented. In this paper, we propose a Model Driven Architecture (MDA)-inspired approach for developing adaptable software. First, we briefly present the component paradigm in which we place our works. Then, we position our component model with regards to related works. In our component model, the interface of the component is described by the way of points of interaction. These points are used to manage different types of interactions between components. The components and the interactions make up a new core model. From our core model, we can build an application model represented by a graph of interactions allowing the integration of the reused components. We finish with the implementation of the application model, thanks to the distributed adaptable software architecture. Each part of this paper is illustrated with a concrete case, the European Aero user-friendly SIMulation-based dIstance Learning (ASIMIL) project.     

CSDL: a language for cooperative systems design

The aim of a cooperative system is to coordinate and support group activities. Cooperative Systems Design Language (CSDL) is an experimental language designed to support the development of cooperative systems from specification to implementation. In CSDL, a system is defined as a collection of reusable entities implementing floor control disciplines and shared workspaces. CSDL tries to address the difficulties of integrating different aspects of cooperative systems: cooperation control, communication, and system modularization. This paper presents CSDL as a specification language. Basic units are coordinators that can be combined hierarchically. A coordinator is composed of a specification, a body, and a context. The specification defines the cooperation policy; the body controls the underlying communication channels; and the context defines coordinators' interaction in modular systems     

Fault Detection and Isolation of discrete-time Markovian jump linear systems with application to a network of multi-agent systems having imperfect communication channels

This paper deals with the problem of Fault Detection and Isolation (FDI) for discrete-time Markovian Jump Linear Systems (MJLSs). A geometric property related to the unobservable subspace of an MJLS is first presented and the concept of unobservability subspace is introduced. Sufficient conditions for designing an H_∞-based FDI algorithm for MJLSs subject to input disturbances and measurement noise are presented and developed. Our proposed approach is then applied to the problem of fault detection and isolation in a network of multi-agent systems when imperfect communication channels exist among the agents. A discrete-time communication link with a stochastic packet dropping effect is considered based on the Gilbert–Elliott model and the entire network is modeled as a discrete-time MJLS. Simulation results are presented for formation flight of satellites to demonstrate and verify the effectiveness and performance capabilities of our proposed FDI algorithm.     

一种可重用构件的设计方法

随着计算机硬件的迅猛发展,软件变得越来越复杂,如何迅速高效地开发出易扩展、易维护、对需求变化具有适应性的软件成为一个急需解决的问题,基于构件的开发是解决这一问题的良好思路,而可重用构件及其结构的设计与优化是其中的关键,首先对现有的构件设施地简要介绍和评价,对构件模型进行卫定义,并给出了玫般情况下构件设计的步骤,然后在此基础上,用定性与定量相结合的方式,给出了玫种标识和设计构件的方法,以及相应的算法     

Back-end manager: an interface between a knowledge-based front end and its application subsystems

Front Ends for Open and Closed User Systems (FOCUS) is an ESPRIT/2 (no. 2620) project aimed at designing tools and techniques for the construction of knowledge-based front ends (KBFEs) for open-user systems (reusable software components, libraries, etc) and closed-user systems (free-standing software, packages, etc). An important part of the project involves the establishment of an architecture for KBFEs and the specification of the KBFE/back-end interface. This paper describes the properties and related issues of such an interface, known as the back-end manager (BEM), and its relationship to the proposed KBFE architecture.     

基于粗糙集支持向量机的网络故障诊断系统

该文针对传统网络故障知识库冗余度高和稳定性难以两全的缺陷,综合运用支持向量机方法和粗糙集理论,提出了RSVM方法,实现不一致情况下的规则获取和学习样本的净化处理。该算法具有简化样本、适应性强、容错性高等特点,能有效处理网络故障诊断中噪声或不相容的信息。由于该方法选择了比SMO更大的工作集而没有增加过多的计算,总的优化步骤减少,收敛速度也更快,平均训练速度约为SMO的两倍。实验表明,利用该方法实现的系统与同类的其他方法相比,提高了诊断准确率和诊断速度。     

A method of qualitative reasoning for model-based problem solving and its application to a nuclear plant

Model-based expert systems are expected to contribute to overcoming the difficulties of conventional rule-based systems. This paper describes the modeling of mechanical systems and a method of qualitative reasoning based on causal specifications. The causal specifications represent a component's local causal properties, following the principles for reusability and composability. It contributes to providing intuitive causal ordering of complex behavior originated in the combination of components, including inter-component negative feedback. A model of a system is represented by combining a set of local component models and global knowledge derived from general properties of the physical entity. This allows for reusable knowledge which is easy to describe. Furthermore, the method has been successfully applied to a nuclear power plant. Reasoning results were unambiguous and matched those obtained by domain experts.     

Co-design of safe networked control systems

Modeling, analysis and control of networked control systems (NCS) have recently emerged as topics of significant interest to the control community. The defining feature of any NCS is that information is exchanged using digital band-limited serial communication channel among systems components and usually shared by other feedback control loops. Conventional control theory with many ideal assumptions, such as synchronized control and non-delayed sensing and actuation must be revisited so that the limitations on communication capabilities within the control design framework can be integrated. Recent achievements showed that it is possible to solve communication problems and control problems simultaneously, thus contributing to a more efficient NCS design. This paper aims at giving an overview of Fault Diagnosis methods dealing with enhancement of robustness against network induced effects and introducing co-design approaches making it possible to solve communication problems and control problems simultaneously, thus contributing to a more efficient design.     

基于虚拟仪器的液压故障诊断系统设计

本文结合军用车辆综合传动装置液压故障诊断的需求设计了液压故障诊断系统。系统设计中结合了LabVIEW和MATLAB的优点,在LabVIEW软件框架下调用MATLAB,实现了系统良好的可操作性和全面的分析功能。     

A neuro-fuzzy multiple-model observer approach to robust fault diagnosis based on the DAMADICS benchmark problem

This paper presents a new framework for fault detection and isolation (FDI) based on neuro-fuzzy multiple modelling together with robust optimal de-coupling of observers. This new paradigm is called the ‘Neuro-Fuzzy and De-coupling Fault Diagnosis Scheme’ (NFDFDS). Multiple operating points are taken care of through the NF modelling framework. The structure also provides residuals that are de-coupled to ‘unknown inputs’, making use of the earlier research on unknown input de-coupling. The NF paradigm exploits the combined abilities of neural networks and fuzzy logic and is an efficient modelling tool for non-linear dynamic systems because of its approximation and reasoning capabilities. The paper also provides a comparative study of NFDFDS with the Extended Unknown Input Observer (EUIO) for FDI, using the DAMADICS benchmark example.