APPLICATION OF FUZZY SET THEORY IN FAULT TREE ANALYSIS

Based on the fuzzy set theory and the expand principle, using fuzzy number as the boundary condition of fault tree analysis, a new method of analyzing fuzzy fault probability of the top event is developed. Fuzzy importance analysis of the basic event is proposed as well. A practical example is given. This method is a new way to solve the obscure problems of fault tree analysis and has great value in engineering practice.

Fuzzy Fault Tree Analysis for Fault Diagnosis of Cannula Fault in Power Transformer

Being one of the most expensive components of an electrical power plant, the failures of a power transformer can result in serious power system issues. So fault diagnosis for power transformer is highly important to ensure an uninterrupted power supply. Due to information transmission mistakes as well as arisen errors while processing data in surveying and monitoring state information of transformer, uncertain and incomplete information may be produced. Based on these points, this paper presents an intelligent fault diagnosis method of power transformer using fuzzy fault tree analysis (FTA) and beta distribution for failure possibility estimation. By using the technique we proposed herein, the continuous attribute values are transformed into the fuzzy numbers to give a realistic estimate of failure possibility of a basic event in FTA. Further, it explains a new approach based on Euclidean distance between fuzzy numbers, to rank the basic events in accordance with their Fuzzy Importance Index.

Study on System Failure Probability Model Based on Dynamic Fault Tree

Aiming at the characteristics of complex logic relation and multiple dynamic gates in system,its failure probability model is established based on dynamic fault tree. For the multi-state dynamic fault tree,it can be transferred into Markov chain with continuous parameters. The state transfer diagram can be decomposed into several state transfer chains,and the failure probability models can be derived according to the lengths of the chains. Then,the failure probability of the dynamic fault tree analysis(DFTA) can be obtained by adding each chain's probability. The failure probability calculation of DFTA based on the continuous parameter Markov chain is proposed and proved. Given an example,the analytic method is compared with the conventional methods which have to solve the differential equation. It is known from the results that the analytic method can be applied to engineering easily.

Reliability assessment of three-dimensional bearing capacity of shallow foundation using fuzzy set theory

The aim of this study is to investigate the applicability of reliability theory on surface square/rectangular footing against bearing capacity failure using fuzzy set theory in conjunction with the finite element method.Soil is modeled as a three-dimensional spatially varying medium,where its parameters(cohesion,friction angle,unit weight,etc.)are considered as fuzzy variables that maintain some membership functions.Soil is idealized as an elastic-perfectly plastic material obeying the Mohr-Coulomb failure criterion,where both associated and non-associated flow rules are considered in estimating the ultimate bearing capacity of the footing.The spatial variability of the soil is incorporated for both isotropic and anisotropic fields,which are determined by the values of scales of fluctuation in both the horizontal and vertical directions.A new parameter namely,limiting applied pressure at zero failure probability is proposed,and it indirectly predicts the failure probability of the footing.The effect of the coefficient of variation of the friction angle of the soil on the probability of failure is analyzed,and it is observed that the effect is significant.Furthermore,the effect of the scale of fluctuation on the probability of failure is investigated,and the necessity for considering spatial variability in the reliability analysis is well proven.

A new approach to fuzzy dynamic fault tree analysis using the weakest n-dimensional t-norm arithmetic

Dynamic fault tree analysis is widely used for the reliability analysis of the complex system with dynamic failure characteristics. In many circumstances, the exact value of system reliability is difficult to obtain due to absent or insufficient data for failure probabilities or failure rates of components. The traditional fuzzy operation arithmetic based on extension principle or interval theory may lead to fuzzy accumulations. Moreover, the existing fuzzy dynamic fault tree analysis methods are restricted to the case that all system components follow exponential time-to-failure distributions. To overcome these problems, a new fuzzy dynamic fault tree analysis approach based on the weakest n-dimensional t-norm arithmetic and developed sequential binary decision diagrams method is proposed to evaluate system fuzzy reliability. Compared with the existing approach,the proposed method can effectively reduce fuzzy cumulative and be applicable to any time-tofailure distribution type for system components. Finally, a case study is presented to illustrate the application and advantages of the proposed approach.

System Reliability Analysis Method Based on T-S FTA and HE-BN

For high-reliability systems in military,aerospace,and railway fields,the challenges of reliability analysis lie in dealing with unclear failure mechanisms,complex fault relationships,lack of fault data,and uncertainty of fault states.To overcome these problems,this paper proposes a reliability analysismethod based on T-S fault tree analysis(T-S FTA)and Hyper-ellipsoidal Bayesian network(HE-BN).The method describes the connection between the various systemfault events by T-S fuzzy gates and translates them into a Bayesian network(BN)model.Combining the advantages of T-S fault tree modeling with the advantages of Bayesian network computation,a reliability modeling method is proposed that can fully reflect the fault characteristics of complex systems.Experts describe the degree of failure of the event in the form of interval numbers.The knowledge and experience of experts are fused with the D-S evidence theory to obtain the initial failure probability interval of the BN root node.Then,the Hyper-ellipsoidal model(HM)constrains the initial failure probability interval and constructs a HE-BN for the system.A reliability analysismethod is proposed to solve the problem of insufficient failure data and uncertainty in the degree of failure.The failure probability of the system is further calculated and the key components that affect the system’s reliability are identified.The proposedmethod accounts for the uncertainty and incompleteness of the failure data in complex multi-state systems and establishes an easily computable reliability model that fully reflects the characteristics of complex faults and accurately identifies system weaknesses.The feasibility and accuracy of the method are further verified by conducting case studies.

FAULT DIAGNOSIS OF ROTATING MACHINERY USING KNOWLEDGE-BASED FUZZY NEURAL NETWORK

A novel knowledge-based fuzzy neural network （KBFNN） for fault diagnosis is presented. Crude rules were extracted and the corresponding dependent factors and antecedent coverage factors were calculated firstly from the diagnostic sample based on rough sets theory. Then the number of rules was used to construct partially the structure of a fuzzy neural network and those factors were implemented as initial weights, with fuzzy output parameters being optimized by genetic algorithm. Such fuzzy neural network was called KBFNN. This KBFNN was utilized to identify typical faults of rotating machinery. Diagnostic results show that it has those merits of shorter training time and higher right diagnostic level compared to general fuzzy neural networks.

Analysis of Syetem Reliability in Manufacturing Cell Based on Triangular Fuzzy Number

Due to lacking of test-data and field-data in reliability research during the design stage of manufacturing cell sys- tem.The degree of manufacturing cell system reliability research is increased.In order to deal with the deficient data and the un- certainty occurred from analysis and judgment,the paper discussed a method for studying reliability of manufacturing cell system through the analysis of fuzzy fault tree,which was based on triangular fuzzy number.At last,calculation case indicated that it would have great significance for ascertaining reliability index,maintenance and establishing keeping strategy towards manufac- turing cell system.

FUZZY PETRI NET FOR FAULT DIAGNOSIS

Because of the stochastic property of fault occurrence and fuzziness offault phenomenon, machine fault diagnosis technique in use, such as fault tree analysis,cause consequence tree method, etc., cannot exactly describe the properties of fault phe-nomenon and coherence of fault space. In this paper, based on the theory of generalPetri net, fault tree technique and theory of fuzzy set, a theory system of fuzzy Petri net(FPN) suitable for fault diagnosis is established, which is applied to an example of faultdiagnosis for FMS. This method has the properties of of rbjectivity, strong expressionability, easy inference, etc., which can solve the problems of stochastic property andfuzziness of fault.

Fuzzy Risk Assessment Model of Power Transformer Based on Borda Number Theory

The power transformer is the key equipment of transforming voltage and exchanging power in the power system.It's safe and reliable operation directly influences the safe level of the power system.To study the risk assessment of power transformer which is very significant to improve the reliability of the power system,a fuzzy comprehensive risk assessment model of power transformer based on Borda number theory is proposed in this paper.At first,the fault types and risk factors of the power transformer are analyzed.Secondly,the basic framework of the fuzzy comprehensive evaluation is applied to quantify the risk factors.And then,Borda number theory is employed to analyze influence degree and occurrence probability of power transformer.At last,the various risk factors impact index and fuzzy comprehensive evaluation index of power transformer can be easily obtained.Applying this model,the relative importance degree of the risk factors can be horizontally compared according to the numerical index,the engineering staff can directly get the parameters of the transformer risk level and get a good description of the visual expression through using 5 score and similar visual language.

基于T-S模糊故障树的驱动电机冷却系统可靠性分析

车用驱动电机液压冷却系统存在故障机理不确定等问题。本文应用模糊数描述其故障概率和故障程度,建立驱动电机冷却系统的T-S模糊故障树模型,计算系统模糊可能性,分析各部件的概率重要度和关键重要度,找出影响系统可靠性的关键部件。

基于故障树和贝叶斯网络的管廊运维风险评估

城市地下综合管廊在运维过程中事故时有发生,为了量化管廊运维风险并分析关键风险因素,提出一种基于故障树和模糊贝叶斯网络的城市地下综合管廊运维风险评估方法。在综合考虑管廊风险因素的基础上构建故障树模型,将其映射为贝叶斯网络。基于ALARP准则划分风险因素状态等级,根据模糊数和模糊子集计算底事件的发生概率,利用最大似然估计法求解中间事件的条件概率,构建管廊运维风险贝叶斯网络模型,精准评估城市地下综合管廊运维风险。结果表明:所评估的管廊运维过程风险等级为High的概率为28%,接近30%的风险阈值,因此需要及时对管廊风险进行管控。该方法能够科学、合理地评价风险水平并确定关键因素,可为管廊运维安全保障和管理提供参考。

Temporal evidence combination method for multi-sensor target recognition based on DS theory and IFS

In order to effectively deal with the conflict temporal evidences without affecting the sequential and dynamic characteristics in the multi-sensor target recognition(MSTR) system at the decision making level, this paper proposes a Dempster-Shafer(DS) theory and intuitionistic fuzzy set(IFS) based temporal evidence combination method(DSIFS-TECM). To realize the method,the relationship between DS theory and IFS is firstly analyzed. And then the intuitionistic fuzzy possibility degree of intuitionistic fuzzy value(IFPD-IFV) is defined, and a novel ranking method with isotonicity for IFV is proposed. Finally, a calculation method for relative reliability factor(RRF) is designed based on the proposed ranking method. As a proof of the method, numerical analysis and experimental simulation are performed. The results indicate DSIFS-TECM is capable of dealing with the conflict temporal evidences and sensitive to the changing of time. Furthermore, compared with the existing methods, DSIFS-TECM has stronger ability of anti-interference.

贫数据条件下燃料电池汽车故障分类方法

燃料电池汽车是未来汽车工业可持续发展的重要方向,但现存燃料电池整车相关的测试评价标准尚未对燃料电池汽车存在的故障类型及其分类进行深入研究,缺乏统一故障分级分类方案。为改善该问题,提出一套完善的燃料电池汽车故障模式的分级分类评价指标以统一相关故障等级,重点研究在缺乏数据条件下的燃料电池汽车故障分类方法。基于因子分析法和模糊集理论,提出一种针对燃料电池汽车在贫数据条件下的故障模式分类评价方法,为燃料电池汽车故障等级的分类提供指导意见。

基于模糊综合评价的水下采油树结构可靠性分析

针对水下采油树结构可靠性分析,提出一种基于模糊综合评价理论的水下采油树结构可靠性分析方法。首先,通过分析不同厂家水下采油树构型,确定水下采油树的典型结构构型及组成,分析水下采油树在运行过程中所受的外载荷;其次,采用专家打分以及模糊综合评价法求得故障树底事件失效率,通过定量分析求解顶事件失效率、可靠度及可靠寿命曲线等可靠性指标;最后,对故障树进行重要度分析及失效率变化对系统结构可靠性的影响,结果表明:“树本体内磨损”的关键重要度最高,对系统结构可靠性的影响最大,是结构中的薄弱环节,应予以关注。研究成果可为水下采油树结构的风险评估提供技术参考,对水下采油树的设计制造提供一定的指导意义。

基于优化故障树模型的液压机械可靠性评估

针对现有液压机械可靠性评估方法存在的评估时间过长、评估结果精度较差等问题,提出基于优化故障树模型的可靠性评估方法。确定液压机械全部故障类型及逻辑关系,建立液压机械故障树模型,采用T-S模糊门取代逻辑门优化故障树模型。利用层次分析法(AHP)测定中间事件重要度,应用T-S模糊门规则对底事件故障概率与模糊数进行设定与计算,获取液压机械故障概率,从而计算出液压机械可靠性评估结果。实验结果显示:该方法的评估时间为4.8 s,液压机械可靠性评估结果与实际结果相同。

Generic Reliability Evaluation Method for Industrial Grids with Variable Frequency Drives

The paper presents a reliability evaluation method based on fault tree analysis with set theory and minimal cut set as core algorithm, which can be used to evaluate the reliability for industrial grids with wide application of variable frequency drives. The working principle is introduced firstly, based on which the method development considering different system topology designs, backup solutions and redundancy mechanisms are analyzed in details. In the end the proposed method is applied to two cases to show the reliability performance of system with variable frequency drives. The proposed method is also suitable for analyzing the reliability performance of industrial grids with other types of power electronic converter technology.

基于模糊故障树和蒙特卡洛方法的智能铲运系统可靠性分析

为了分析智能铲运系统在三山岛矿区内实际运行使用的可靠性,提出将模糊故障树分析与蒙特卡洛仿真相结合的研究方法。以智能铲运系统运行使用故障为顶事件,确定了16个中间事件和33个底事件,并构建了故障树模型。采用模糊集合理论的方法,通过10位专家的结果反馈,求取了各底事件的发生概率,进而对故障树进行了定量分析,得到顶事件发生概率为0.3481%。基于建立的故障树模型,采用蒙特卡洛仿真模拟的方法,编写蒙特卡洛仿真算法,合理设置仿真参数,最后得到了平均无故障时间、可靠性与不可靠性曲线以及系统失效概率曲线。通过对底事件的仿真重要度进行计算,结果表明:操作规范不合格(管理原因)和信息沟通失误(人员原因)对系统可靠性影响最大,影响最大的机械原因为操作装置故障和制动系统老化。通过将计算结果与实际数据进行对比分析,验证了该方法的准确性和有效性。

改进综合因子法的数控伺服刀架可靠性分配方法

针对可靠性分配过程中影响因素和专家打分的不确定性问题,提出一种将灰色关联理论、模糊集理论和有序加权平均算子结合的基于改进综合因子法的数控伺服刀架可靠性分配方法。综合考虑技术水平、重要度、复杂度、运行环境、维修性、费效比等多种影响因素,将各因素细化并分层,建立分层的综合因子评价模型,并给出评价标准。综合现场试验得到的统计数据,建立子系统的全局指标模型,得到每个子系统的全局指标,以故障率为分配指标将数控刀架系统的总体故障率分配到各子系统,实现数控伺服刀架的可靠性分配,得到的可靠度分配结果为驱动系统2.193×10-5、传动装置1.645×10-5、锁紧松开及定位装置2.547×10-5、刀盘信号装置盘1.345×10-5、密封与紧固装置4.589×10-5和连接线与连接界面4.544×10-5,与数控伺服刀架的工程实际情况相符。

基于ECE-FFTA法的舰船航空保障系统易损性评估方法研究

为合理地评估武器攻击下舰船毁伤效应,本文基于模糊集理论,将专家综合评价与模糊故障树分析相结合,建立了一种舰船航空保障系统易损性评估方法,解决了复杂系统分析过程存在的评价语言模糊性和认知不确定性问题。分析了航空保障系统组成与各子系统的毁伤逻辑,针对典型毁伤模式进行了模糊综合评价,构建并求解了航空保障系统模糊故障树,开展了爆炸冲击后航空保障系统的易损性评估。结果表明:以系统失效率和基本事件重要度作为易损性评估指标,可以定量地表征武器攻击后航空保障系统的毁伤程度。研究成果对于舰船航空保障系统防护设计和其他重要系统的易损性评估具有借鉴意义。