浙江电网继电保护设备评价管理系统的构建

浙江电网继电保护设备评价管理系统目标在于针对各个厂家的设备运行数据,进行客观的评价考核,形成对各厂家各设备的评价体系,为继电保护设备的管理和选型工作建立标准。系统采用开发J2EE技术,基于Struts＋Spring＋Hibernate的经典MVC架构,使用AJAX技术以提高前台展现效果。文章阐述了继电保护设备评价管理系统的物理结构和总体技术框架,详细描述了功能模块的划分,分析了关键技术（数据同步技术、jQuery、工作流技术与模板引擎技术、JACOB和POI等）在系统中的应用。系统为继电保护状态检修的辅助决策以及设备选型与管理等工作提供了重要手段,有效地提高了电网的信息化管理水平。     

基于模型驱动架构的工作流管理系统开发研究

针对企业在导入或转换新的工作流平台时重新建模的问题,提出基于MDA的工作流管理系统开发架构.此架构中工作流程的建模分成两个阶段,首先设计了工作流程的PIM元模型并进行PIM建模,然后将PIM转换成PSM模型,最后再由PSM自动产生流程定义文件,这样在转移工作流程平台时,流程的PIM模型可以保留并以模型转换技术对应至新平台的PSM模型.给出了由PIM元模型转换为WfMC PSM模型的程序以及由WfMC PSM模型转换为XPDL流程定义的程序,并以电子订单工作流程为例进行了验证.此开发架构降低了流程平台转移时的成本与复杂度,提高了工作流程模型的可重用性.     

基于UML扩展的数据仓库多维数据PIM建模

针对数据仓库多维数据PIM建模问题,对多维数据模型维和事实进行了定义.在UML(Unified Modeling Language)扩展的基础上,提出了与多维模型相关的八个版类,从而可以对数据仓库中PIM模型的各种情况进行图形化描述.最后基于某钢铁企业采购系统的采购价格差异分析主题进行了建模.     

浅谈继电保护系统的状态检修

传统的继电保护检验有很大的强制性和盲目性，没有考虑设备的实际情况。为了满足大电网运行的要求，有必要采取一种新的维修方式来提高系统的可靠性水平及设备的可用率。对电力系统的继电保护系统进行基于状态监测、状态评估及实时维修决策的状态检修势在必行。     

装备测试性设计辅助决策系统关键技术研究

针对测试性设计的辅助决策工具是装备测试性设计水平提高的关键技术。围绕测试性设计辅助决策系统实现,从装备测试性设计建模、装备测试性设计与分析优化算法、辅助决策系统实现等三个方面展开研究,在分析现有模型的基础上提出了用于测试性设计的信息模型建模思想,并对测试性设计过程中的诊断优化算法进行了研究,最后完成对测试性模型、诊断策略的集成,对系统平台实现的关键技术进行了研究。本研究是实现装备测试性设计辅助决策系统的关键。     

基于MDA的ODP互操作性软件过程研究

利用RM-ODP概念架构，提出了基于MDA的ODP软件过程，将互操作性的实现贯穿于整个系统的开发过程之中：在PIM中设计，在PSM中实现。为了使系统建立在正确的完整的PIM之上，在需求分析阶段采用了EDOC模式进行可视化的建模，在功能设计阶段采用了ELOTOS形式化描述得到PIM。因此，本软件过程实现了ODP系统基于可测试业务模型的互操作性。     

基于角色模型构建的平台无关模型

MDA把模型分为PIM和PSM，通过PIM到PSM的转换，实现PIM的重用。如何构建PIM是一个重要课题，该文提出了一个基于角色模型的PIM建模方法。该方法首先建立系统用况的角色模型，然后通过角色的组合和分配约束，把角色模型转换成类模型，在不同抽象层次实现模型的重用。最后通过一个Web Application的建模过程说明该方法的使用。     

一种基于面向方面机制的模型转换方法

传统对象建模技术生成的PIM(Model Driven Architecture)一般是多重关注点混杂在一起的大型模型,该模型会导致PIM到PSM(Platform Specific Model)的模型转换工作较为困难.提出了一种基于面向方面机制的模型转换方法,该方法在模型层将系统横切关注点与核心关注点分离,单独建模为方面子模型,给出了方面PIM到方面PSM的转换规则,改进了对象建模生成的模型在转换中关注点混杂和对横切关注点管理的不足.     

建模技术在作战辅助决策系统开发中的应用

针对海军某作战辅助决策系统业务规则复杂、功能齐全的特点,依照模型驱动开发(Modeling-driyen Development,MDD)的思想,采用UML建立该系统的需求和结构模型,使用相关工具构建基本框架.建模技术贯穿系统设计和实现的全过程,可以控制和管理前期文档与图表,使其与系统开发同步.     

军用飞机保障能力评价建模与仿真

在对军用飞机维修保障过程分析的基础上，运用离散事件建模方法和计算机建模与仿真技术建立了飞机维修保障仿真模型。仿真出飞机使用可用度（A0）、出动架次率（SGR）、备件延误时间（SDT）、系统无故障工作时间（MTBF）等指标，来评价保障能力。仿真模型可以量化分析影响军用飞机保障能力的各种因素，显示、预测保障系统运行状态，提供辅助决策。通过改变任务计划、备件策略、维修策略。做动态敏感性分析。可以评价不同方案的维修保障能力，改进现有维修保障系统。仿真模型目前应用于航空兵部队团级保障能力评价，今后还将对未定型飞机开展维修保障仿真验证。     

基于Web和数据仓库的信息系统构架

首先分析了企业事务处理活动与决策支持活动的关系,研究了用数据仓库集成事务处理系统与决策支持系统的系统结构和运行机制,最后给出了基于Web的管理信息系统框架。     

Integrated system health management-oriented maintenance decision-making for multi-state system based on data mining

To ensure a series of missions can be completed with only finite breaks, many systems are required to guarantee system safety and mission success. Of these, maintenance decision support is vital. One widely used maintenance strategy has been selective maintenance. Most traditional selective maintenance optimisation research has focused on binary state systems, which are subject to distribution deterioration or failure. However, a majority of systems used in aerospace or industrial applications are multi-state systems with more than two states deteriorating at the same time, meaning that real-time state distribution is needed to provide more timely and effective maintenance. This paper presents a novel integrated system health management-oriented maintenance decision support methodology and framework for a multi-state system based on data mining. An aero-engine system numerical example is given to illustrate the methodology, the results of which demonstrate the significant advantages of using data mining to efficiently obtain state distribution information, and the benefits of using a robust optimal model to choose suitable strategies. This methodology, which is applicable to multi-state systems of varying sizes, has the ability to solve maintenance problems when imperfect maintenance quality is considered.     

Adaptive decision support systems

The effectiveness of decision support systems (DSS) is enhanced through dynamic adaptation of support to the needs of the decision maker, to the problem, and to the decision context. We define this enhanced DSS as adaptive decision support systems (ADSS) and propose its architecture. In an ADSS, the decision maker controls the decision process. However, the system monitors the process to match support to the needs. The proposed architecture evolves from the traditional DSS models and includes an additional intelligent‘Adaptation’ component. The ‘Adaptation’ component workd with the data, model, and interface components to provide adaptive support. The architecture also integrates enhancements proposed in the past research. In this paper, we have illustrated the proposed architecture with two examples, a prototype system, and results from a preliminary empirical investigations     

Production line simulation using STPN for maintenance scheduling

As the complexity of manufacturing systems keeps escalating, the maintenance decision making becomes increasingly challenging. Simulation has become an effective way to avoid costly decisions through what-if analysis of different maintenance policies, and maintenance schedules before their actual implementation. In this paper, a new modularized simulation package for manufacturing production systems has been developed using standard Stochastic Timed Petri-Nets (STPNs). By utilizing the basic functional modules, we can quickly build production lines with different configurations and maintenance policies. A maintenance decision support tool has also been developed in this paper, together with the simulation package, to provide offline and online maintenance decision support. Copyright © 2007 IFAC.     

基于马尔可夫过程的多部件系统劣化状态空间划分模型

工业系统的复杂性及智能化程度的不断提高使得系统的可靠性和安全性严重制约着系统正常的工作运转.长时间的工作运行会加大系统的故障风险,降低其安全稳定性.为了减少系统故障给产品质量和生产成本带来的影响,系统的最优维修决策问题逐渐成为研究的热点.分析系统的劣化状态有利于对系统做出正确的维修决策,延长系统的运行时间及减少经济损失.针对相同且劣化独立的多个部件组成的系统,建立离散状态建模下的多部件系统的多状态联合劣化空间划分模型.通过联合劣化状态空间的划分,给出所有维修需求组合及其概率计算通式,运用马尔科夫过程理论建立系统状态的平稳概率模型,并通过数值实验验证了该模型的正确性和有效性.     

试论计算机网络信息管理与决策支持系统体系结构设计

本文从开发软件系统的理论与实践出发，探讨了在微型计算机网络系统上开发信息管理与决策支持系统应采用的一般体系结构，并简述了这种结构模式对减少应用软件系统的维护，防止软件危机发生的重要作用．     

Condition-based maintenance of dynamic systems using online failure prognosis and belief rule base

Condition-based maintenance has attracted an increasing attention both academically and practically. If the required physical models to describe the dynamic systems are unknown and the monitored information only reflects part of the state of the dynamic systems, expert knowledge is a source of valuable information to be used. However, expert knowledge is usually in a qualitative form, and therefore, needs to be transformed and combined with the measured characteristic information to provide effective prognosis. As such, this paper focuses on developing a novel approach to deal with the problem. In the proposed approach, a belief rule base (BRB) for the failure prognostic model is constructed using the expert knowledge and the analysis of the failure mechanism. An online failure prognostic algorithm is then proposed on the basis of the currently available characteristic variable information. The failure prognostic model is finally used in a condition based decision model to support the replacement decision of the dynamic systems. A case example is examined to demonstrate the implementation and potential applications of the proposed failure prognostic algorithm and the condition-based replacement model.     

一种演化超图文法到状态转移系统的映射方法

运用模型检测技术验证动态演化的正确性,是近年来软件体系结构动态演化研究领域面临的一个挑战.然而,当前的方法很少考虑软件体系结构动态演化时的相关条件.针对该问题,提出用条件状态转移系统表示软件体系结构动态演化的状态模型,将软件体系结构超图映射为状态,演化规则运用映射为条件状态转移关系,给出软件体系结构动态演化的条件超图文法到条件状态转移系统的映射方法以及相应的实现算法,实现了软件体系结构动态演化的条件状态转移系统的构建,并证明了在该映射方法下,软件体系结构动态演化条件超图文法与条件状态转移系统的互模拟等价.最后通过案例分析,运用该方法以及模型检测技术,验证了软件体系结构动态演化的相关性质,从而验证了该方法的有效性.     

Pluralistic multi-agent decision support system: a framework and an empirical test

Recent research in decision support systems (DSSs) has focused on building active cooperative intelligent systems. Research in agent-based decision support is a promising stream in this direction. This paper proposes a framework for a pluralistic multi-agent decision support system (MADSS). The distinguishing feature of the proposed approach is its organization around human decision making process. The framework builds upon the decision support pyramid with agents organized into groups according to the phases of the problem solving model. We outline the design principles and develop architecture for MADSS. The framework is illustrated through an investment MADSS prototype. The results of the empirical test are presented.     

决策支持系统结构框架的研究

该文在分析决策支持系统DSS体系结构的基础上,提出了集成数据仓库、知识仓库、模型仓库作为底部架构的DSS新体系结构,并详细阐述其特色和模型仓库新概念以及实现的关键技术。该架构有效解决了模型同客观事物发展不一致问题,简化了模型获得和编码任务,增强了决策的有效性和智能性,提高了决策的效率,表明了DSS技术发展的趋势。