概率行为树模型转化为模型检测模型方法研究

将概率模型检测方法运用到机电系统可靠性评价中,可以有效提高可靠性分析特别是FMEA分析的准确性与效率。利用概率模型检测对机电系统进行可靠性评价需要对机电系统进行形式化建模,直接利用模型检测语言对系统进行形式化建模直观性较差,建模难度大。对机电系统的概率行为树建模进行了介绍,分析了概率模型检测工具PRISM提供的形式化建模语言,定义了从概率行为树模型到PRISM形式化模型的转换规则,实现了机电系统概率行为树模型向模型检测形式化模型的转换。以数控机床工作台系统为例验证了转换方法的可行性。     

一种基于FMEA的故障网络图自动构建方法研究

针对复杂机电系统故障网络图(FG)模型构建问题,对失效模式和效果分析(FMEA)的方法进行了研究,对FMEA故障模式关联影响和逻辑关系进行了分析,对故障关联矩阵和其形式化表达之间的关系进行了归纳,提出了一种基于FMEA的从故障关联矩阵到FG模型的自动构建方法。利用大型空压机组进行了层次结构分解和故障模式影响的故障网络图的自动构建试验。研究结果表明:该方法能够有效提高FG构建的准确性和效率,可用于对复杂机电系统故障诊断建立准确的FG模型。     

机电系统的概率行为树建模及可靠性评价

直接利用模型检测工具提供的形式化语言对系统进行形式化建模直观性较差、建模难度大,因此利用概率行为树对机电系统进行形式化建模,并通过概率模型检测对机电系统进行可靠性评价。对机电系统功能执行过程中功能载体的状态及其变迁进行了研究。基于概率行为树的语义和句法,提出了机电系统状态变迁过程的概率行为树建模方法,开发了建模支持工具。利用该建模工具可实现机电系统的概率行为树建模并能将其转换为基于PRISM语言的形式化模型。基于机电系统的潜在故障,用连续随机逻辑对机电系统可靠性评价指标进行形式化规约。基于概率行为树模型和可靠性评价指标的形式化规约,利用模型检测工具PRISM实现了对机电系统的可靠性评价。该方法比直接使用形式化语言建模更直观、易于理解和掌握。     

基于IDEF的复杂机电系统状态解析

利用功能-行为-状态建模思想,提出了基于IDEF的复杂机电系统状态解析方法。首先利用IDEF0建立复杂机电系统功能结构的形式化表达,然后基于功能-行为映射关系并根据行为之间的时序、逻辑关系利用IDEF3建立复杂机电系统行为过程的形式化表达,最后将系统行为过程形式化表达模型中的行为单元的行为映射为状态,形成复杂机电系统的状态变迁网络。基于状态变迁网络,可以获得复杂机电系统行为过程中的状变迁序列,进而实现复杂机电系统的状态解析。     

基于粗糙集-田口质量观的失效模式与影响分析

针对目前失效模式与影响分析（FMEA）方法中对实际风险较大的失效模式的风险难以有效评估的问题,提出了一种基于粗糙集理论和质量损失函数的FMEA新方法。首先,在对潜在失效模式进行分析的基础上,通过专家系统构建失效模式风险评估矩阵模型;其次,以降低数据本身的主观性和模糊性为目标,基于粗糙集理论将风险评估矩阵模型转换成粗糙域矩阵模型;再次,根据求解的粗糙域矩阵,运用多元质量损失函数模型,对每一个失效模式的潜在损失进行求解,依据潜在损失的大小对失效模式风险进行排序。最后,以发动机装配过程为例,对其失效模式与影响进行分析,并将其分析结果与目前的FMEA方法比较,验证了所提出方法的合理性和有效性。     

基于概率模型检测的机电系统动态可靠性评价

为克服传统动态可靠性分析方法的不足,提出基于概率模型检测的机电系统动态可靠性评价方法。介绍了概率模型检测的概念及概率模型检测工具PRISM。用形式化建模语言描述系统单元的状态变迁过程,建立了机电系统的形式化模型。利用连续随机逻辑对机电系统可靠性评价指标进行形式化描述,建立了可靠性指标的规约表达式,借助概率模型检测工具自动解算可靠性指标,实现了基于概率模型检测的机电系统动态可靠性评价。所提方法建模过程简单,能有效提高机电系统动态可靠性分析的效率。     

模糊DEMATEL算法在安全性分析中的应用

考虑到在传统安全性分析方法中存在难以用准确数据描述系统的失效状态、确定失效模式优先级的问题,提出了将决策试验与评估实验室法(DEMATEL)和模糊集理论相结合的模糊DEMATEL算法,并将其应用到故障模式和影响分析法(FMEA)中。由专家对故障模式进行评价,借以模糊数的形式表示出来,计算得到各故障原因的原因度,确定影响因素。以民机货舱的动力驱动单元(PDU)为例进行了应用,通过改进的FMEA对故障树分析法(FTA)的分析结论进行验证,结果表明该方法有效地提高了安全性分析的可靠性和经济性,同时具有一定的通用性,为各工程领域的安全性分析提供了有力参考。     

基于NARX网络模型的挖掘机液压系统故障检测

提出了一种针对挖掘机液压系统的非线性有源自回归(nonlinear auto-regressive with extrainputs,NARX)网络模型的故障检测方法。NARX网络模型是一种将有源自回归(auto-regressivewith extra inputs,ARX)模型与神经网络相结合的系统建模方法,具有很强的非线性辨识能力。该方法首先选取合理的网络模型结构,并根据AIC准则确定最佳模型阶数;使用正常状态样本对NARX网络进行训练,建立系统的辨识模型;然后运用序贯概率比检验(sequential probability ratiotest,SPRT)对NARX辨识模型的残差进行假设检验,检测系统的故障状态。实验分析表明,基于NARX网络模型的故障检测方法能够有效地应用于挖掘机液压系统。     

一种基于MFM的传感器优化配置方法

为了解决大型流程工业系统状态监测故障诊断系统的传感器优化配置问题,基于多级流模型(MFM)的传感器优化配置,在多级流模型分析的基础上,提出了一种改进的失效模式与影响分析(FMEA)方法.以故障可检测性及可分辨性作为约束函数,利用测点-故障敏感度、传感器可靠性及成本系数构造了一种新的复合优化目标函数,建立传感器优化配置模型并给出了优化算法,最后给出了电站除氧器实例.分析结果表明该方法的可行性和有效性.     

基于FMEA与FTA的合膛检测设备可靠性分析

针对弹药自动化生产过程中合膛检测设备可靠运行问题,提出了基于FMEA(Failure mode and effects analysis,失效模式影响分析)与FTA(Fault Tree Analysis,故障树分析)的合膛检测设备可靠性分析方法。分析了合膛检测设备的组成及运行过程,完成了合膛检测设备故障模式及失效成因分析,并采用措施优先级(AP)方法构建了自动合膛检测设备的FMEA表,确定了关键可能的潜在失效模式以及后果,完成了基于FTA的自动合膛检测设备的故障树分析。通过建立磨损模型,计算了不同装配检测次数下的自动合膛检测设备的可靠度。所提方法可以为弹药自动生产装配过程中合膛设备的可靠运行及维护等提供依据,提升了自动合膛检测设备的稳定性。     

Failure Mode and Effect Analysis (FMEA) Over the WWW

Failure mode and effect analysis (FMEA) is one of the formal techniques for effective product development. Its main purpose is to avoid as many potential failures as possible by identifying them and taking appropriate actions in the early stages of design and development. Stand-alone FMEA software packages are commercially available in the market. They offer limited support for teamwork. This paper proposes to employ the World Wide Web (WWW, web) technology to provide FMEA services on the internet/intranets. Resulting web-based FMEA systems require no installation or maintenance but offer remote and simultaneous access and therefore better teamwork.     

Diagnostics and prognostics based on adaptive time-frequency feature discrimination

This paper presents a novel diagnostic technique for monitoring the system conditions and detecting failure modes and precursors based on wavelet-packet analysis of external noise/ vibration measurements. The capability is based on extracting relevant features of noise/ vibration data that best discriminate systems with different noise/vibration signatures by analyzing external measurements of noise/vibration in the time-frequency domain. By virtue of their localized nature both in time and frequency, the identified features help to reveal faults at the level of components in a mechanical system in addition to the existence of certain faults. A prima-facie case is made via application of the proposed approach to fault detection in scroll and rotary compressors, although the methods and algorithms are very general in nature. The proposed technique has successfully identified the existence of specific faults in the scroll and rotary compressors. In addition, its capability of tracking the severity of specific faults in the rotary compressors indicates that the technique has a potential to be used as a prognostic tool.     

A computer-integrated FMEA for dynamic supply chains in a flexible-based environment

Quality management (QM) for dynamic supply chains (DSCs) in a flexible-based environment has received increasing attention in current business environment. This study focuses on the development of an QM tool, based on the failure modes and effects analysis (FMEA) approach, and demonstrates how it can be extended from application in supply chain management (SCM) to other business environments. The main contributions are to implement an iterative process using FMEA for DSCs in a flexible-based environment by overcoming the weaknesses associated with traditional FMEA system and to develop a user-friendly interface, with which the distributed parties in chains could cooperate as a whole and meet the needs of dynamic control. In specific, this paper proposes a computer-integrated FMEA approach that enhanced FMEA in SCM through automated processing using a fuzzy approach and a computer-integrated and internet-based interface to support the system implementation. The efficiency and practical implication of the proposed system has been validated by the developed system with a case study. The developed system can help prevent possible failures in the design and operations and, furthermore, the assurance of quality for DSCs in a flexible-based environment. The proposed system may easily be extended to more complex real-world applications.     

Module-based Failure Propagation (MFP) model for FMEA

Failure mode and effect analysis (FMEA) is one of the most important activities in the quality management of product design. Within the field of product development domain, FMEA is regarded as a key driver for product quality improvement and cost reduction. There have been various FMEA approaches considering several aspects such as knowledge management, criticality analysis, and product structure or function model to conduct more effective and systematic FMEA. But previous approaches are generally based on an ad hoc model so that they have limitations such as insufficient identification on failures, low reusability of previous FMEAs, poor understanding on failure information, high dependency of expert knowledge on failure propagation, and so on. To overcome these limitations, this study proposes a formalized function model for FMEA, which is named module-based failure propagation (MFP) model. The MFP model is proposed based on the function behavior state scheme. The MFP model consists of function decomposition tree model, configuration flow graph model, function rule, and failure rule. This study describes how to build the MFP model and introduces how to carry out FMEA with the proposed MFP model. To show the benefit of the proposed MFP model, a FMEA case study on a car air purifier is performed.     

提高大型复杂机电系统故障诊断质量的几种新方法

分析了大型复杂机电系统故障的可诊断性问题,探讨了影响故障可诊断性的主要因素及其评价标准,研究了HHT(Hilbert/Huang transform)时频分析方法在提高大型复杂机电系统诊断信息质量中的应用。为了进一步提高诊断系统对未知故障的诊断质量,分析讨论了自组织特征映射、生成拓扑映射,以及曲元分析等无监督机器学习算法在大型复杂机电系统故障诊断中的应用。针对故障信号的非线性特征以及多类复杂故障的线性不可分问题,结合机器学习领域的最新研究成果,探讨了基于核的机械故障特征提取方法与基于核的故障模式分类方法,并对采用核方法分析设备运行状态的趋势变化作了初步探讨。     

Indirect adaptive fuzzy fault-tolerant tracking control for MIMO nonlinear systems with actuator and sensor failures

In this paper, an active fuzzy fault tolerant tracking control (AFFTTC) scheme is developed for a class of multi-input multi-output (MIMO) unknown nonlinear systems in the presence of unknown actuator faults, sensor failures and external disturbance. The developed control scheme deals with four kinds of faults for both sensors and actuators. The bias, drift, and loss of accuracy additive faults are considered along with the loss of effectiveness multiplicative fault. A fuzzy adaptive controller based on back-stepping design is developed to deal with actuator failures and unknown system dynamics. However, an additional robust control term is added to deal with sensor faults, approximation errors, and external disturbances. Lyapunov theory is used to prove the stability of the closed loop system. Numerical simulations on a quadrotor are presented to show the effectiveness of the proposed approach.     

正交试验下基于FMMESA和GRA的环境应力-故障关联分析

环境应力是导致机电系统故障的主要原因,环境应力因素与机电系统故障间存在复杂的关联关系。首先,在故障模式、机理及影响分析方法的基础上,提出故障模式、机理、环境应力分析方法,用于定性分析导致机电系统故障的环境应力因素。其次,以定性分析结论为指导,应用加权评判法和正交试验设计法优化设计环境应力试验方案。然后,以试验数据为基础,应用灰色系统理论,提出环境应力特征与故障灰色关联分析方法,用于定量分析环境应力及其特征与故障的关联关系。最后,进行案例应用与分析。实验结果表明,所提出的方法能在优化后的试验次数情况下定性并定量的分析出影响系统故障的主要环境应力及其特征,可用于指导机电系统测试性虚拟试验中的环境建模、环境应力等级评定等,还可以作为故障检测、诊断与预测的信息基础。     

基于部分可观察马尔可夫决策过程的机电装备动态可靠性评价方法

针对机电装备运行维护问题,提出了基于部分可观察马尔可夫决策过程(POMDP)理论的动态可靠性评价方法。该方法将可靠性动态演变看成POMDP问题,通过不完全观测到的设备运行信息（如噪声、温度、压力等）,对可靠性状态进行估计,同时分析不同的维修行为对可靠性水平的影响规律,构建了基于状态转移的动态可靠性评价模型。然后,提出了以最小化维修成本费用和潜在故障危害为目标的维护策略制定方法,并通过案例分析验证了该方法的有效性,实现了机电装备动态可靠性的有效评价与维护策略的科学制订。