计算智能在故障诊断专家系统中的应用

基于知识的专家系统及其在故障诊断中的应用研究十分活跃,形成一类故障诊断专家系统,但该方法存在知识获取的瓶颈、推理能力弱及难于处理不确定知识等问题,其进一步发展受到严重的阻碍。与此同时,神经网络、模糊逻辑和遗传算法等计算智能在近年来却取得了一系列的进展,并具有专家系统等符号智能所缺乏的优势。将计算智能应用到专家系统中即与符号智能相结合起来能有效地解决诊断专家系统的难题,该文对此进行了探讨,并提出了一些新的思路。     

Fault detection and identification in an intelligent restructurable controller

The fault detection and identification problem in an intelligent restructurable controller is addressed using a combination of algorithmic and artificial intelligence methods. An architecture is developed to address this problem. The integration of a variety of distinct knowledge representations and diagnostic reasoning techniques, and the system design and implementation is facilitated by the introduction of a novel knowledge representation graph.     

基于模糊推理的物流车辆故障诊断专家系统

物流车辆故障诊断专家系统可以对物流车辆的故障进行诊断和排除. 为了提高该系统快速、准确诊断的能力, 在分析物流车辆的故障模式和故障机理的基础上, 建立故障树, 采用改进的CLIPS可以进行正向、反向两种模糊推理机制, 同时建立知识库管理系统对模糊规则和事实进行管理. 研究结果表明: 改进的CLIPS与VC++的结合, 使物流车辆故障诊断专家系统拥有模糊诊断故障的能力, 提高了物流车辆故障诊断的智能化水平.     

Inventing a Biologically Inspired, Energy Efficient Micro Aerial Vehicle

In recent years, research efforts have focused on the design, development and deployment of unmanned systems for a variety of applications ranging from intelligence and surveillance to border patrol, rescue operations, etc. Micro Aerial Vehicles are viewed as potential targets that can provide agility and accurate small area coverage while being cost-effective and can be easily launched by a single operator. The small size of MAVs allows such flight operations within confined space but the control effectors must provide sufficient maneuverability, while maintaining stability, with only limited sensing capability onboard the platform. To meet these challenges, researchers have long been attracted by the amazing attributes of biological systems, such as those exhibited by birds and insects. Birds can fly in dense flocks, executing rapid maneuvers with g-loads far in excess of modern fighter aircrafts, and yet never collide with each other, despite the absence of air traffic controllers. This paper introduces a novel framework for the design and control of a Micro Air Vehicle. The vehicle’s conceptual design is based on biologically-inspired principles and emulates a dragonfly (Odonata–Anisoptera). A sophisticated multi-layered Hybrid & Linear/Non-Linear controller to achieve extended flight times and improved agility compared to other Rotary and Flapping Wing MAV designs. The paper addresses the design and control features of the proposed QV design and gives an overview on the developmental efforts towards the prototyping of the flyer. The potential applications for such a high endurance vehicle are numerous, including air-deployable mass surveillance in cluster and swarm formations. The disposable nature of the vehicle would help in battle-field deployment as well, where such a MAV would be made available to soldiers for proximity sensing and threat level assessment. Other applications would include search and rescue operations and civilian law-enforcement.     

基于故障树的发射车故障诊断技术研究

针对目前发射车电气系统故障定位复杂、缺少快速定位分析手段、问题排查必须依赖研制专家、排故时间长的问题,设计了一种基于故障树的诊断机制对发射车进行故障诊断。建立了发射车故障树,设计了基于算法和规则的配置方法将检测数据与故障树节点相关联,采用基于最小割集的快速诊断推理技术,完成了对发射车的故障自动诊断。试验结果表明,该方法实现了发射车电气系统故障的快速自动诊断定位,诊断定位准确,具有较好的实用性。     

基于连续故障模型的Delta算子系统可靠鲁棒H_∞控制

研究具有执行器故障的Delta算子线性不确定系统的可靠鲁棒H_∞问题.设计控制器,确保在执行器发生故障时闭环系统仍能保持鲁棒稳定,且满足给定的H_∞指标.针对执行器连续故障模型,运用线性矩阵不等式方法,得到Delta算子系统α-次优可靠鲁棒H_∞状态反馈控制器的存在条件和设计方法,并进一步给出了Delta算子系统最优可靠鲁棒H_∞控制器的设计方法.数值算例表明,该设计方法是有效而可行的.

Abstract：

The reliable robust H_∞ control problem is studied for the Delta operator systems with actuator failure.The purpose is to design a controller which can tolerate actuator failures,such that the Delta operator closed-loop system is asymptotic stable for all admissible uncertainties,and the H_∞-performance index of the closed-loop system is less than a given upper bound.A more practical model of actuator failure,continuous failure model,is considered.A sufficient condition for the existence of the state feedback α-suboptimal reliable robust H_∞ controllers is derived by using the linear matrix inequality approach.Then the design procedures of such controllers and optimal reliable robust H_∞ controllers are proposed respectively.A numerical example demonstrates the effectiveness and feasibility of the design methods.     

航空电子系统故障管理体系结构研究

军用航空电子系统承载着战机绝大多数作战任务,是决定战机作战效能的重要因素.故障管理体系结构及技术是保证航空电子系统和战机安全性的重要技术之一.概述了航空电子系统含义、功能分配结构及功能与资源的映射关系,总结了航空电子系统顶层设计原则,可指导故障管理体系的构建.探讨故障管理的含义和任务,论述联合式和IMA两类航电系统故障管理结构,并就其共性问题进行探讨.最后试探性地提出故障管理体系结构需进一步研究和解决的问题.     

Monitoring and fault diagnosis of hybrid systems.

Many networked embedded sensing and control systems can be modeled as hybrid systems with interacting continuous and discrete dynamics. These systems present significant challenges for monitoring and diagnosis. Many existing model-based approaches focus on diagnostic reasoning assuming appropriate fault signatures have been generated. However, an important missing piece is the integration of model-based techniques with the acquisition and processing of sensor signals and the modeling of faults to support diagnostic reasoning. This paper addresses key modeling and computational problems at the interface between model-based diagnosis techniques and signature analysis to enable the efficient detection and isolation of incipient and abrupt faults in hybrid systems. A hybrid automata model that parameterizes abrupt and incipient faults is introduced. Based on this model, an approach for diagnoser design is presented. The paper also develops a novel mode estimation algorithm that uses model-based prediction to focus distributed processing signal algorithms. Finally, the paper describes a diagnostic system architecture that integrates the modeling, prediction, and diagnosis components. The implemented architecture is applied to fault diagnosis of a complex electro-mechanical machine, the Xerox DC265 printer, and the experimental results presented validate the approach. A number of design trade-offs that were made to support implementation of the algorithms for online applications are also described.     

AI-ESTATE故障树诊断模型的建立及工具开发

AI-ESTATE标准是人工智能技术应用于测试与诊断领域的国际通用标准,对测试环境下的诊断知识以及服务进行了规范化的表述,以实现诊断推理系统间兼容性,诊断知识的可互换性和可移植性。介绍了AI-ESTATE标准及其体系结构、模型构成,深入研究故障树模型构成要素,提出了符合XML Schema的标准化故障树建模方法;利用COM组件技术开发了相应的配置工具,实现了故障树模型自动配置,进而实现诊断知识共享、重用。     

带有随机丢包的空间关联系统的控制

研究当子系统之间信息传输存在随机丢包时空间关联系统的分析和设计问题. 通过引入空间移动算子和时间前向移动算子, 将关联系统建模为具有Markovian跳变参数的关于离散时间和空间变量的多维线性系统, 其中以Markovian跳变参数反映通信信道的状态, 得到整个关联系统在某一给定丢包率下适定且均方稳定的解析条件. 提出一种分布式动态输出反馈控制器的设计方法, 该控制器和被控对象具有相同的空间关联结构, 并基于线性矩阵不等式方法求解. 最后通过一个具有通信丢包影响的多机编队控制系统实例进一步阐明该模型及方法的正确性和有效性.     

基于免疫原理的故障诊断推理模型研究

智能故障诊断系统作为人工智能技术在故障诊断领域的应用,在实践中取得了较好的成效,但随着系统设备和功能的日益复杂化,各种故障现象成因越来越复杂,同时异常故障也时有发生,现有固定的诊断推理模型却难以满足复杂系统诊断面临的全部要求。针对故障诊断系统中常规固定诊断推理模型难以适应动态变化环境的缺点,该文在分析生物体免疫应答过程中免疫细胞协作机制基础上,采用多Agent技术构建了一种具有进化重构特性、适合于复杂系统故障问题求解的诊断推理模型,并给出了其工作流程。     

A diagnosis scheme for a large-scale system

This paper presents a method for diagnosis in a large-scale system environment. The method utilizes the theory of hierarchical systems and hybrid diagnostic reasoning from AI (artificial intelligence). In shallow reasoning, which is a part of hybrid reasoning, the concept of entropy is used to determine which component (that might be responsible for a symptom observed) is to be tested next. The procedure is illustrated using a simulated example of a CIM (computer-integrated manufacturing) system, and is implemented on IntelliCorp's knowledge engineering environment (KEE).     

网络故障诊断关键技术

由于网络故障不可避免,这就要求对网络出现的故障进行管理。但是网络故障信息通常表现出复杂和不确定性的特点,要准确的对故障进行检测和定位是相当困难的,特别是故障定位。重点分析了故障定位的原理基础上．介绍了利用专家系统、神经网络和贝叶斯网络等人工智能技术,对症状和故障之间的因果关系进行推理的故障定位技术。     

Combining FDI and AI approaches within causal-model-based diagnosis.

This paper presents a model-based diagnostic method designed in the context of process supervision. It has been inspired by both artificial intelligence and control theory. AI contributes tools for qualitative modeling, including causal modeling, whose aim is to split a complex process into elementary submodels. Control theory, within the framework of fault detection and isolation (FDI), provides numerical models for generating and testing residuals, and for taking into account inaccuracies in the model, unknown disturbances and noise. Consistency-based reasoning provides a logical foundation for diagnostic reasoning and clarifies fundamental assumptions, such as single fault and exoneration. The diagnostic method presented in the paper benefits from the advantages of all these approaches. Causal modeling enables the method to focus on sufficient relations for fault isolation, which avoids combinatorial explosion. Moreover, it allows the model to be modified easily without changing any aspect of the diagnostic algorithm. The numerical submodels that are used to detect inconsistency benefit from the precise quantitative analysis of the FDI approach. The FDI models are studied in order to link this method with DX component-oriented reasoning. The recursive on-line use of this algorithm is explained and the concept of local exoneration is introduced.     

An integrated case-based reasoning approach for intelligent help desk fault management

As modern business functions become more complex and knowledge-intensive, with increasing demands for quality services, there is an emerging trend for organisations to develop and deploy intelligent knowledge-based systems for mission-critical operations. Some of the challenges in successfully implementing this breed of systems depend on how well the intelligent system is integrated with conventional existing information systems and workflow, and the quality of the intelligent system itself. Developing quality expert systems lies in the effective modelling of cognitive processes of human experts and representation of various forms of related knowledge in a domain. An integrated intelligent system called the Intelligent Help Desk Facilitator (IHDF), has been developed for computer and network fault management. The system, which comprises various modules including an expert system, is successfully deployed in a problem response help desk environment of a local bank. This paper describes a cognitive-driven approach to the development of the expert system based on a hybrid knowledge representation and reasoning strategy. The approach incorporates a hybrid case-based reasoning (CBR) framework of techniques which include case memory organisation structures (discrimination networks and shared-featured networks), case indexing and retrieval schemes (fuzzy character-matching, nearest-neighbour similarity matching and knowledge-guided indexing); and an interactive and incremental style of reasoning. The paper discusses the design and implementation of the expert system component of IHDF and illustrates the appropriateness of the hybrid architecture for problem resolution and diagnostic types of applications.     

线性时滞系统的耗散控制

研究了一类线性时滞系统的二次耗散控制问题,基于线性矩阵不等式（LMI）方法导出了耗散控制器存在的充分条件,通过线性矩阵不等式的可行解构造出耗散态状态反馈和动态输出反馈控制律,相应的闭环系统是二次稳定和严格（Q,S,R）耗散的,本文的主要贡献是统一了线性时滞系统现有的H∞控制和无源控制结果。     

一类不确定广义系统的分散容错控制

讨论一类不确定广义系统分散容错控制器设计问题.首先利用线性矩阵不等式(LMI)设计分散状态反馈控制器,使得广义系统执行器未出现故障时渐近稳定;接着针对广义系统的部分执行器出现故障的情况设计分散状态反馈控制器,使得闭环广义系统渐近稳定;进而利用LMI设计广义系统在分散状态反馈作用下具有完整性的容错控制器;同时对传感器故障情形设计了广义系统在分散输出反馈作用下具有完整性的容错控制器,得到了不确定广义系统关于执行器和传感器的分散容错控制器设计的方法.将所设计的控制器用于实际电子网络系统,验证了所提出方法的有效性.     

Modeling and real-time simulation architectures for virtual prototyping of off-road vehicles

Virtual Reality-based simulation technology has evolved as a useful design and analysis tool at an early stage in the design for evaluating performance of human-operated agricultural and construction machinery. Detecting anomalies in the design prior to building physical prototypes and expensive testing leads to significant cost savings. The efficacy of such simulation technology depends on how realistically the simulation mimics the real-life operation of the machinery. It is therefore necessary to achieve ‘real-time’ dynamic simulation of such machines with operator-in-the-loop functionality. Such simulation often leads to intensive computational burdens. A distributed architecture was developed for off-road vehicle dynamic models and 3D graphics visualization to distribute the overall computational load of the system across multiple computational platforms. Multi-rate model simulation was also used to simulate various system dynamics with different integration time steps, so that the computational power can be distributed more intelligently. This architecture consisted of three major components: a dynamic model simulator, a virtual reality simulator for 3D graphics, and an interface to the controller and input hardware devices. Several off-road vehicle dynamics models were developed with varying degrees of fidelity, as well as automatic guidance controller models and a controller area network interface to embedded controllers and user input devices. The simulation architecture reduced the computational load to an individual machine and increased the real-time simulation capability with complex off-road vehicle system models and controllers. This architecture provides an environment to test virtual prototypes of the vehicle systems in real-time and the opportunity to test the functionality of newly developed controller software and hardware.     

Hybrid knowledge bases

Deductive databases that interact with, and are accessed by, reasoning agents in the real world (such as logic controllers in automated manufacturing, weapons guidance systems, aircraft landing systems, land-vehicle maneuvering systems, and air-traffic control systems) must have the ability to deal with multiple modes of reasoning. Specifically, the types of reasoning we are concerned with include, among others, reasoning about time, reasoning about quantitative relationships that may be expressed in the form of differential equations or optimization problems, and reasoning about numeric modes of uncertainty about the domain which the database seeks to describe. Such databases may need to handle diverse forms of data structures, and frequently they may require use of the assumption-based nonmonotonic representation of knowledge. A hybrid knowledge base is a theoretical framework capturing all the above modes of reasoning. The theory tightly unifies the constraint logic programming scheme of Jaffar and Lassez (1987), the generalized annotated logic programming theory of Kifer and Subrahmanian (1989), and the stable model semantics of Gelfond and Lifschitz (1988). New techniques are introduced which extend both the work on annotated logic programming and the stable model semantics     

Design of two-layer switching rule for stabilization of switched linear systems with mismatched switching

A two-layer switching architecture and a two-layer switching rule for stabilization of switched linear control systems are proposed, under which the mismatched switching between switched systems and their candidate hybrid controllers can be allowed. In the low layer, a state-dependent switching rule with a dwell time constraint to exponentially stabilize switched linear systems is given; in the high layer, supervisory conditions on the mismatched switching frequency and the mismatched switching ratio are presented, under which the closed-loop switched system is still exponentially stable in case of the candidate controller switches delay with respect to the subsystems. Different from the traditional switching rule, the two-layer switching architecture and switching rule have robustness, which in some extend permit mismatched switching between switched subsystems and their candidate controllers.