武器装备基于状态的维修系统设计

为了减少武器装备的故障以及维修时间,提高武器装备的可用度和重要部件的使用寿命,采用基于状态的维修技术与方法已成为当前维修领域研究与应用的热点.从武器装备的维修需求与技术出发,分析了现行装备维修的主要方式及其优缺点,总结了当前基于状态的维修(CBM)研究与应用现状,在此基础上提出了武器装备基于案例的CBM系统框架,给出了CBM适用的条件,并对CBM系统的核心模块进行了分析,给出了CBM系统工作的流程.最后,结合某装备中一齿轮箱的状态检测信息,进行了基于声音的装备故障诊断与案例分析与决策.分析结果表明:基于案例的CBM系统简单实用,能够满足装备维修需求.     

基于输变电设备风险评估的维修决策*

针对目前输变电设备的维修技术,将风险评估引入输变电设备的维修决策中,建立了基于风险评估的维修方法,应用于输变电设备的基本技术框架。从经济风险和系统风险两方面出发,分别得到设备量化的各个风险指标。通过对系统风险进行经济性量化,将输变电设备故障造成的系统后果可以由相应的系统严重度来表示。最后的算例分析验证了该方法能够更加全面科学地评估风险,更加快速有效地进行维修决策。     

基于状态维修过程中的故障预测问题分析

故障预测作为基于状态维修实现的关键,可以有效支持维修管理者的决策。参照国际标准化组织对故障预测的定义,划分故障预测过程,提出预测方法性能评估至少存在的两种方式,在分类和比较现有预测方法的基础上,明确预测方法的适用范围和限制条件,为工程预测系统的构建提供参考。     

电站设备状态评价与维修决策系统开发与应用

为了解决电站设备在实际运行过程中因运行工况复杂导致难以对设备可靠性水平进行有效地分析评价,且电站设备在后续维修过程中存在临时性检修频繁、维修不足、维修过剩、盲目维修等问题,因此开发了一套电站设备状态评价与维修决策系统。以机器学习作为算法支撑,结合热工专业知识建立基于数据驱动的热工过程模型,并利用该模型对现场运行设备进行实时在线状态监测和评估,为维修决策和故障诊断提供基础信息,对于科学指导发电辅助设备乃至机组运行管理和维修决策具有重要意义。     

基于状态的维修及其建模研究

基于状态的维修（Condition Based Maintenanec,CBM）是设备（武器系统）预报初始故障的主动维修的一种形式。是设备维修的重耍发展方向之一,也是本世纪初国内外维修领域研究的热点课题。为进一步推进CBM理论在国内的研究与应用,该文首先介绍了CBM的概念,分析了其在技术上的可行性,与定期（时）维修作比较,说明了CBM的优越性。其次,重点构造了单状态信息的CBM的模型,该模型实现了预防性维修的优化决策。最后,给出了该模型仿真软件的结构框图,该文对CBM理论的进一步研究具有十分重要的意义。     

基于可靠性理论的状态维修决策模型研究

维修时机的选择是状态维修的主要任务之一.为准确预测设备最佳维修时机,根据直到当前时刻的设备监测信息,利用可靠性理论与随机滤波理论,建立了设备可靠度预测模型及以单位时间内总的停机时间期望值和单位时间平均费用为组合优化目标的状态维修决策模型.模型克服了以单位时间内最小维修费用等为优化目标的设备状态维修决策模型的局限性,提高...     

基于状态的类测试研究

类是面向对象程序语言的基本组成单位,所以类测试是整个面向对象软件测试的关键所在;论文主要针对传统状态测试方法在发现错误机制上存在的不足,研究了一种利用OSD模型的基于状态的类测试方法,提出了利用OSD模型与系统分析设计的状态图模型进行比较的思想;通过比较两个状态图模型中的状态是否一致以及各个状态间的方法转移是否一致,来发现传统状态测试难以发现的错误;实践证明,该方法能够检测出传统的状态测试方法难以检测到的错误。     

基于构件的HLA系统开发

HLA作为新一代分布交互仿真体系结构,已对我军作战仿真开发产生了深刻影响,但HLA系统开发的复杂性和联邦成员的有限重用性大大限制了HLA应用的广泛性。该文分析了产生这些问题的根源,详细探讨了基于构件开发(CBD)的技术特点和实现途径,研究了CBD方法在HLA开发的应用,提出了基于HLA的仿真构件模型及其实现思路,阐明了实现的关键环节和方法,最后介绍了研究中的一些思考。     

健康状态评估方法及应用研究

随着设备越来越复杂、经济可承受性要求越来越高,评估设备的健康状态就显得尤为重要;健康状态评估技术是实现状态维修的重要手段之一;论述了健康状态评估在状态维修中的地位和作用;分析了国内外健康状态评估的主要方法,主要包括模型法、层次分析法、模糊评判法、人工神经网络法、基于贝叶斯网络的方法等;接着介绍了健康状态评估技术的工程应用情况;最后,详细分析了我国在健康状态评估研究中存在的问题,并指出了进一步研究的重点方向。     

一种智慧地铁轨道状态预测和维修决策优化系统

为提高地铁轨道智能化管理水平,设计了一种新的智慧地铁轨道管理系统;分别设计了朴素贝叶斯分类器、Logistic回归分类器和支持向量机分类器,并构建了基于Stacking集成算法的轨道状态预测模型;利用XX地铁1号线、2号线和6号线在2015-2021年的设备数据、检测数据和维修数据,验证了模型有效性;引入自适应学习的马尔可夫决策过程(AL-MDP),构建了基于Stacking-SVM的轨道维修决策优化模型;利用模型对地铁轨道进行运行状态感知和异常状态预测,通过自适应学习的过程不断学习地铁轨道的劣化机理,并且为轨道的状态预警和维修策略提供个性化、精细化的决策建议;最后,设计并实现了智慧地铁轨道管理系统;引入AL-MDP后进一步降低地铁轨道的维修成本,能够实时掌握地铁轨道的运作状态;该研究给管理者和工作者提供精细化、个性化、更科学的维修优化决策,对维修成本和轨道安全实现双重精准控制。     

Accuracy and robustness of decision making techniques in condition based maintenance

This paper presents a study on Type I and Type II errors that are inherent in every technique for decision making in condition based maintenance. Specifically, the study considers those errors that result when three methods are used for decision making: the control charts known as the Statistical Process Control, the Hidden Markov Model, and the Proportional Hazard Model. The objective is to study the accuracy and the robustness of these techniques to variations in the models’ parameters. Monte Carlo simulation is used to simulate the performance of these techniques. The effects of parameter’s variations are obtained through Taguchi’s design of experiments, and the results are analyzed by the analysis of variance technique. Those results show that accuracy and robustness should be taken into consideration when maintenance decisions are taken. Optimization techniques can be used to optimize the values of the parameters in order to minimize the two types of errors and to increase the correct decisions.     

相依多模失效下冷贮备系统最优切换及视情维护决策

针对存在冲击影响的冷贮备系统,研究其最优切换及视情维护决策问题.首先,在系统结构和切换式运行和维护特性分析的基础上,制定基于周期切换和状态检测的切换式离线视情维护策略;其次,建立累积冲击过程影响下系统退化所致的软失效和极端冲击过程所致的硬失效竞争可靠性模型;再次,通过分析两类冲击过程影响下系统运行与备用设备交替使用、维修过程中的状态转移特性,重点推导各检测周期时刻系统状态概率分布的迭代计算模型;然后,以系统平均费用率最小为目标,建立解析决策模型,以求解系统的最优切换周期和维护阈值.最后,以矿井主通风系统为案例验证策略及模型的有效性,并分析模型对参数的灵敏度.结果表明,系统的最优维修策略随机冲击影响的不同而变化显著.     

Application of the condition based maintenance checking system for aircrafts

Condition Based Maintenance (CBM) systems have evolved as an effective health and usage monitoring mechanism in aircrafts by reducing the costs associated with unscheduled maintenance. CBM systems help maintainers to detect and manage the condition of aviation system components and take maintenance actions when there is evidence of need. In this paper we describe the application of a software prototype, which is an automation of the CBM practices. We briefly explain the novel framework on which it is built. We illustrate the building of the configuration information, required to generate the maintenance reports that are deemed essential for continuous improvement under CBM, using a markup language called XML. We explain the procedure in generating the reports using the developed prototype. We demonstrate that the developed prototype has the functional capabilities essential to implement CBM on any aircraft and is valuable in cutting down the software maintenance costs as it can perform new operations without having to modify the existing source codes.     

基于预知维修的开放式状态监测系统的实现

在“预知维修”的设备管理体制的构想下,构建了一种基于因特网、面向设备管理的开放式机械设备状态监测与故障诊断系统,该系统在建立远程专家状态监测与故障诊断体系的同时,与企业设备管理信息系统有机地融合,可以为设备管理部门及时提供现场设备运行状况,并通过设备故障诊断网和设备管理信息网实现了设备管理和状态监测的无缝结合。详细地介绍了系统的构成方式和思路,并通过天津某大型电厂的应用证明了它的实用性和准确性。     

Review,analysis and synthesis of prognostic-based decision support methods for condition based maintenance

In manufacturing enterprises, maintenance is a significant contributor to the total company’s cost. Condition based maintenance (CBM) relies on prognostic models and uses them to support maintenance decisions based on the predicted condition of equipment. Although prognostic-based decision support for CBM is not an extensively explored area, there exist methods which have been developed in order to deal with specific challenges such as the need to cope with real-time information, to predict the health state of equipment and to continuously update maintenance-related recommendations. The current work aims at providing a literature review for prognostic-based decision support methods for CBM. We analyse the literature in order to identify combinations of methods for prognostic-based decision support for CBM, propose a practical technique for selecting suitable combinations of methods and set the guidelines for future research.     

基于RCM的雷达装备维修决策支持系统研究

针对传统RCM(reliability centered maintenance)分析存在的信息利用不充分、缺乏模型支持及实施过程不够完整等不足,提出了雷达装备RCM分析的信息化改进思路。在分析了改进的RCM过程模型基础上,设计出雷达装备维修决策支持系统。以数据的充分利用和模型的合理支持为核心,描述了系统的逻辑全貌。基于分布式网络技术和面向服务软件技术构建了开放式、智能化的系统应用体系构架。原型系统开发结果表明,该方案能充分利用各类有用信息,在相关模型支持下,实现更规范、更快捷、更准确的装备维修分析与决策。     

基于网络的变电站远程维护系统的开发

通过对变电站远程维护系统开发现状的分析，提出了变电站远程维护系统需要实现的功能。应用电力远动技术和计算机远程控制技术，实现了一个变电站远程维护系统原型，为今后使用系统的开发应用提供了思路和启发。     

维修智能决策支持系统及其可视化实现

阐速了一种维修智能决策支持系统的可视化实现，讨论了决策支持可视化的涵义，介绍了可视化维修智能决策支持系统的体系结构及关键技术。该系统支持自动获取维修数据信息，实现了维修故障诊断过程和智能决策的可视化，提高了装备维修保障水平。     

Development of decision support knowledge based system for tool wear diagnosis

This paper deals with the problems faced by small and medium sized metal cutting industries, with the perspective of tool monitoring. In a small or medium size metal cutting industry employing major metal cutting process, one of the primary problem is that of tool monitoring and wear diagnosis. The problem is of immediate concern especially in those industries where the processes or operations employed are flexible and production depends entirely on orders from customers. Due to a flexible manufacturing setup, almost all major metal cutting processers need to be carried out. However, it becomes increasingly difficult for such small or medium size metal cutting industries to employ skilled manpower for each operation as well as expert technicians to supervise the operation, and carry out fault diagnosis and tool monitoring. Also, the problem associated with tool monitoring is that human operator carrying out the monitoring has to rely either on observation such as ceasing of tool, rise in temperature, generation of fumes, noisy operation, vibrations, considerable change in shape etc, or by monitoring the quality of the finished product. Also, there can be instances where the operator does notice a symptom but does not have the expertise to identify the cause of the trouble. Errors in tool monitoring can lead to considerable damage both to the machine as well as the workpiece. On the other hand, if the tool is replaced before it reaches its useful life expectancy, it leads to unnecessary additional cost. A Decision Support Knowledge Based System (DSKBS) has therefore been developed in this paper with the above considerations. The DSKBS provides the user with a friendly environment to diagnose a particular tool wear and obtain the necessary repair or replacement instructions. The goal is to increase productivity, decrease cost of operation and enhance total quality and reliability of the operation.