Lubricant diagnosis serves as a crucial accordance for condition-based maintenance(CBM)involving oil changing and wear examination of critical parts in equipment.However,the accuracy of traditional end-to-end diagnosi...Lubricant diagnosis serves as a crucial accordance for condition-based maintenance(CBM)involving oil changing and wear examination of critical parts in equipment.However,the accuracy of traditional end-to-end diagnosis models is often limited by the inconsistency and random fluctuations in multiple monitoring indicators.To address this,an attribute-driven adaptive diagnosis method is developed,involving three attributes:physicochemical,contamination,and wear.Correspondingly,a fuzzy fault tree(termed FFT)-based model is constructed containing the logic correlations from monitoring indicators to attributes and to lubricant failures.In particular,inference rules are integrated to mitigate conflicts arising from the reverse degradation of multiple indicators.With this model,the lubricant conditions can be accurately assessed through rule-based reasoning.Furthermore,to enhance its intelligence,the model is dynamically optimized with lubricant analysis knowledge and monitoring data.For verification,the developed model is tested with lubricant samples from both the fatigue experiment and actual aero-engines.Fatigue experiments reveal that the proposed model can improve the lubricant diagnosis accuracy from 73.4%to 92.6%compared with the existing methods.While for the engine lubricant test,a high accuracy of 90%was achieved.展开更多
Some ideas in the development of fault diagnosis system for spacecraft are introduced. Firstly, the architecture of spacecraft fault diagnosis is proposed hierarchically with four diagnosis frames, i.e., system level,...Some ideas in the development of fault diagnosis system for spacecraft are introduced. Firstly, the architecture of spacecraft fault diagnosis is proposed hierarchically with four diagnosis frames, i.e., system level, subsystem level, component level and element level. Secondly, a hierarchical diagnosis model is expressed with four layers, i.e., sensors layer, function layer, behavior layer and structure layer. These layers are used to work together to accomplish the fault alarm, diagnosis and localization. Thirdly, a fault-tree-oriented hybrid knowledge representation based on frame and generalized rule and its relevant reasoning strategy is put forward. Finally, a diagnosis case for spacecraft power system is exemplified combining the above with a powerful expert system development tool G2.展开更多
针对应急通信车通信网络综合组网复杂性和故障关联关系复杂性越来越高的问题,提出了基于故障树分析(Fault Tree Analysis,FTA)法的应急通信车通信网络故障集中诊断方法。该方法可以实现通信网络故障的快速诊断,并能够将诊断结果反馈到...针对应急通信车通信网络综合组网复杂性和故障关联关系复杂性越来越高的问题,提出了基于故障树分析(Fault Tree Analysis,FTA)法的应急通信车通信网络故障集中诊断方法。该方法可以实现通信网络故障的快速诊断,并能够将诊断结果反馈到应急通信车智能通信网络管控系统,通过故障专家知识库支撑和资源调控智能化辅助,实现人工干预或通信网络自适应快速调整和恢复,从而提升应急通信车可靠性、维修性水平。该设计方法可推广应用到大型复杂通信系统和通信、指挥车辆平台通信网络的运维管理系统中,具有较广阔的设计分析和工程应用前景。展开更多
Expert knowledge is the key to modeling milling fault detection systems based on the belief rule base.The construction of an initial expert knowledge base seriously affects the accuracy and interpretability of the mil...Expert knowledge is the key to modeling milling fault detection systems based on the belief rule base.The construction of an initial expert knowledge base seriously affects the accuracy and interpretability of the milling fault detection model.However,due to the complexity of the milling system structure and the uncertainty of the milling failure index,it is often impossible to construct model expert knowledge effectively.Therefore,a milling system fault detection method based on fault tree analysis and hierarchical BRB(FTBRB)is proposed.Firstly,the proposed method uses a fault tree and hierarchical BRB modeling.Through fault tree analysis(FTA),the logical correspondence between FTA and BRB is sorted out.This can effectively embed the FTA mechanism into the BRB expert knowledge base.The hierarchical BRB model is used to solve the problem of excessive indexes and avoid combinatorial explosion.Secondly,evidence reasoning(ER)is used to ensure the transparency of the model reasoning process.Thirdly,the projection covariance matrix adaptation evolutionary strategies(P-CMA-ES)is used to optimize the model.Finally,this paper verifies the validity model and the method’s feasibility techniques for milling data sets.展开更多
Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a ...Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.展开更多
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 uncertaint...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.展开更多
Innovations for electric vehicles have advanced quickly in latest decades. Large-scale business use of these vehicles is still constrained by reliability-related issues. By utilising fault tree (FT) and Monte Carlo si...Innovations for electric vehicles have advanced quickly in latest decades. Large-scale business use of these vehicles is still constrained by reliability-related issues. By utilising fault tree (FT) and Monte Carlo simulation, a mathematical prototype is created that includes the reliability traits of all major electrical parts of the vehicle system, including the battery, motor, drive, controllers. The research demonstrates that by raising the component restoration rates, the vehicle’s survivability can be raised. A thorough discussion of this paradigm is provided, along with a presentation and analysis of the reliability estimations based on an electric vehicle. This research on the reliability design and maintenance of an electric vehicle can be supported by the ideas that are outlined in the paper. Additionally, the findings of this study may be helpful to those who build electric vehicle, especially when upgrading the components efficiency and planning for reliability increase.展开更多
大众迈腾发动机不能起动的影响因素错综复杂,需要寻求一种新的方法来提高诊断的有效性。故障树分析法(Fault Tree Analysis,FTA)为科学诊断电控发动机这种复杂的动力机械提供了新思路。以起动控制逻辑作为构建故障树的基础,分析了迈腾B8...大众迈腾发动机不能起动的影响因素错综复杂,需要寻求一种新的方法来提高诊断的有效性。故障树分析法(Fault Tree Analysis,FTA)为科学诊断电控发动机这种复杂的动力机械提供了新思路。以起动控制逻辑作为构建故障树的基础,分析了迈腾B8L2.0T发动机从按下E378到起动机驱动齿轮带动飞轮旋转的整个过程,建立了“起动机不能运转”和“起动机运转但发动机不能起动”故障树,依据各个事件内在的控制规律设计了故障诊断流程。实验结果表明:故障树模型符合大众迈腾发动机的工作机理,根据故障诊断流程能够准确锁定迈腾发动机不能起动的故障部位。展开更多
为进一步提高大型游乐设施使用安全性,以大型游乐设施事故为研究对象,提出了融合故障树分析法(Fault Tree Analysis,FTA)、层次分析法(Analytic Hierarchy Process,AHP)和逼近理想解决策方法(Technique for Order Preference by Similar...为进一步提高大型游乐设施使用安全性,以大型游乐设施事故为研究对象,提出了融合故障树分析法(Fault Tree Analysis,FTA)、层次分析法(Analytic Hierarchy Process,AHP)和逼近理想解决策方法(Technique for Order Preference by Similari-ty to Ideal Solution,TOPSIS)的事故预防方案决策分析。定性定量地分析了大型游乐设施事故危险因素的影响程度,量化了事故预防措施方案以及决策过程。结果表明,在摩天轮坠落事故中,基本事件X3维修保养不到位和X4检查不到位对事故发生的影响程度最高,二者均属于安全制度因素。急需优先采取的事故预防方案为方案6,包括避免乘客和操作人员不安全行为,应对室外不利环境,完善安全制度和提高应急救援能力等措施。展开更多
This paper presents an approximate algorithm based on simulated annealing to achieve the maximum probability of the minimal cut sets for a fault tree. Near optimal minimal cut sets and important sequence of the basic ...This paper presents an approximate algorithm based on simulated annealing to achieve the maximum probability of the minimal cut sets for a fault tree. Near optimal minimal cut sets and important sequence of the basic events are also solved by the method. Computer simulations show that the algorithm performs very well.展开更多
基金supported in part by the National Natural Science Foundation of China(Nos.52275126 and 52105159)the Science and Technology Planning Project of Shaanxi Province,China(No.2024GX-YBXM-292).
文摘Lubricant diagnosis serves as a crucial accordance for condition-based maintenance(CBM)involving oil changing and wear examination of critical parts in equipment.However,the accuracy of traditional end-to-end diagnosis models is often limited by the inconsistency and random fluctuations in multiple monitoring indicators.To address this,an attribute-driven adaptive diagnosis method is developed,involving three attributes:physicochemical,contamination,and wear.Correspondingly,a fuzzy fault tree(termed FFT)-based model is constructed containing the logic correlations from monitoring indicators to attributes and to lubricant failures.In particular,inference rules are integrated to mitigate conflicts arising from the reverse degradation of multiple indicators.With this model,the lubricant conditions can be accurately assessed through rule-based reasoning.Furthermore,to enhance its intelligence,the model is dynamically optimized with lubricant analysis knowledge and monitoring data.For verification,the developed model is tested with lubricant samples from both the fatigue experiment and actual aero-engines.Fatigue experiments reveal that the proposed model can improve the lubricant diagnosis accuracy from 73.4%to 92.6%compared with the existing methods.While for the engine lubricant test,a high accuracy of 90%was achieved.
文摘Some ideas in the development of fault diagnosis system for spacecraft are introduced. Firstly, the architecture of spacecraft fault diagnosis is proposed hierarchically with four diagnosis frames, i.e., system level, subsystem level, component level and element level. Secondly, a hierarchical diagnosis model is expressed with four layers, i.e., sensors layer, function layer, behavior layer and structure layer. These layers are used to work together to accomplish the fault alarm, diagnosis and localization. Thirdly, a fault-tree-oriented hybrid knowledge representation based on frame and generalized rule and its relevant reasoning strategy is put forward. Finally, a diagnosis case for spacecraft power system is exemplified combining the above with a powerful expert system development tool G2.
文摘针对应急通信车通信网络综合组网复杂性和故障关联关系复杂性越来越高的问题,提出了基于故障树分析(Fault Tree Analysis,FTA)法的应急通信车通信网络故障集中诊断方法。该方法可以实现通信网络故障的快速诊断,并能够将诊断结果反馈到应急通信车智能通信网络管控系统,通过故障专家知识库支撑和资源调控智能化辅助,实现人工干预或通信网络自适应快速调整和恢复,从而提升应急通信车可靠性、维修性水平。该设计方法可推广应用到大型复杂通信系统和通信、指挥车辆平台通信网络的运维管理系统中,具有较广阔的设计分析和工程应用前景。
基金This work was supported in part by the Natural Science Foundation of China under Grant 62203461 and Grant 62203365in part by the Postdoctoral Science Foundation of China under Grant No.2020M683736+3 种基金in part by the Teaching reform project of higher education in Heilongjiang Province under Grant Nos.SJGY20210456 and SJGY20210457in part by the Natural Science Foundation of Heilongjiang Province of China under Grant No.LH2021F038in part by the graduate academic innovation project of Harbin Normal University under Grant Nos.HSDSSCX2022-17,HSDSSCX2022-18 andHSDSSCX2022-19in part by the Foreign Expert Project of Heilongjiang Province under Grant No.GZ20220131.
文摘Expert knowledge is the key to modeling milling fault detection systems based on the belief rule base.The construction of an initial expert knowledge base seriously affects the accuracy and interpretability of the milling fault detection model.However,due to the complexity of the milling system structure and the uncertainty of the milling failure index,it is often impossible to construct model expert knowledge effectively.Therefore,a milling system fault detection method based on fault tree analysis and hierarchical BRB(FTBRB)is proposed.Firstly,the proposed method uses a fault tree and hierarchical BRB modeling.Through fault tree analysis(FTA),the logical correspondence between FTA and BRB is sorted out.This can effectively embed the FTA mechanism into the BRB expert knowledge base.The hierarchical BRB model is used to solve the problem of excessive indexes and avoid combinatorial explosion.Secondly,evidence reasoning(ER)is used to ensure the transparency of the model reasoning process.Thirdly,the projection covariance matrix adaptation evolutionary strategies(P-CMA-ES)is used to optimize the model.Finally,this paper verifies the validity model and the method’s feasibility techniques for milling data sets.
基金financially supported by the National Ministry of Industry and Information Technology Innovation Special Project-Engineering Demonstration Application of Subsea Production System,Topic 4:Research on Subsea X-Tree and Wellhead Offshore Testing Technology(Grant No.MC-201901-S01-04)the Key Research and Development Program of Shandong Province(Major Innovation Project)(Grant Nos.2022CXGC020405,2023CXGC010415)。
文摘Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.
基金the National Natural Science Foundation of China(51875073).
文摘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.
文摘Innovations for electric vehicles have advanced quickly in latest decades. Large-scale business use of these vehicles is still constrained by reliability-related issues. By utilising fault tree (FT) and Monte Carlo simulation, a mathematical prototype is created that includes the reliability traits of all major electrical parts of the vehicle system, including the battery, motor, drive, controllers. The research demonstrates that by raising the component restoration rates, the vehicle’s survivability can be raised. A thorough discussion of this paradigm is provided, along with a presentation and analysis of the reliability estimations based on an electric vehicle. This research on the reliability design and maintenance of an electric vehicle can be supported by the ideas that are outlined in the paper. Additionally, the findings of this study may be helpful to those who build electric vehicle, especially when upgrading the components efficiency and planning for reliability increase.
文摘大众迈腾发动机不能起动的影响因素错综复杂,需要寻求一种新的方法来提高诊断的有效性。故障树分析法(Fault Tree Analysis,FTA)为科学诊断电控发动机这种复杂的动力机械提供了新思路。以起动控制逻辑作为构建故障树的基础,分析了迈腾B8L2.0T发动机从按下E378到起动机驱动齿轮带动飞轮旋转的整个过程,建立了“起动机不能运转”和“起动机运转但发动机不能起动”故障树,依据各个事件内在的控制规律设计了故障诊断流程。实验结果表明:故障树模型符合大众迈腾发动机的工作机理,根据故障诊断流程能够准确锁定迈腾发动机不能起动的故障部位。
文摘为进一步提高大型游乐设施使用安全性,以大型游乐设施事故为研究对象,提出了融合故障树分析法(Fault Tree Analysis,FTA)、层次分析法(Analytic Hierarchy Process,AHP)和逼近理想解决策方法(Technique for Order Preference by Similari-ty to Ideal Solution,TOPSIS)的事故预防方案决策分析。定性定量地分析了大型游乐设施事故危险因素的影响程度,量化了事故预防措施方案以及决策过程。结果表明,在摩天轮坠落事故中,基本事件X3维修保养不到位和X4检查不到位对事故发生的影响程度最高,二者均属于安全制度因素。急需优先采取的事故预防方案为方案6,包括避免乘客和操作人员不安全行为,应对室外不利环境,完善安全制度和提高应急救援能力等措施。
文摘This paper presents an approximate algorithm based on simulated annealing to achieve the maximum probability of the minimal cut sets for a fault tree. Near optimal minimal cut sets and important sequence of the basic events are also solved by the method. Computer simulations show that the algorithm performs very well.
