As an important technology for predictive maintenance, failure prognosis has attracted more and more attentions in recent years. Real-time reliability prediction is one effective solution to failure prognosis. Conside...As an important technology for predictive maintenance, failure prognosis has attracted more and more attentions in recent years. Real-time reliability prediction is one effective solution to failure prognosis. Considering a dynamic system that is composed of normal, deteriorating and unreliable components, this paper proposes an integrated approach to perform real-time reliability prediction for such a class of systems. For a deteriorating component, the degradation is modeled by a time-varying fault process which is a linear or approximately linear function of time. The behavior of an unreliable component is described by a random variable which has two possible values corresponding to the operating and malfunction conditions of this component. The whole proposed approach contains three algorithms. A modified interacting multiple model particle filter is adopted to estimate the dynamic system＇s state variables and the unmeasurable time-varying fault. An exponential smoothing algorithm named the Holt＇s method is used to predict the fault process. In the end, the system＇s reliability is predicted in real time by use of the Monte Carlo strategy. The proposed approach can effectively predict the impending failure of a dynamic system, which is verified by computer simulations based on a three-vessel water tank system.展开更多
A useful life prediction method based on the integration of the stochastic hybrid automata(SHA) model and the frame of the dynamic fault tree(DFT) is proposed. The SHA model can incorporate the orbit environment, work...A useful life prediction method based on the integration of the stochastic hybrid automata(SHA) model and the frame of the dynamic fault tree(DFT) is proposed. The SHA model can incorporate the orbit environment, work modes, system configuration, dynamic probabilities and degeneration of components,as well as spacecraft dynamics and kinematics. By introducing the frame of DFT, the system is classified into several layers, and the problem of state combination explosion is artfully overcome.An improved dynamic reliability model(DRM) based on the Nelson hypothesis is investigated to improve the defect of cumulative failure probability(CFP), which is used to address the failure probability of components in the SHA model. The simulation using the Monte-Carlo method is finally conducted on two satellites, which are deployed with the same multi-gyro subsystem but run on different orbits. The results show that the predicted useful life of the attitude control system(ACS) with consideration of abrupt failure,degradation, and running environment is quite different between the two satellites.展开更多
Aiming to the puzzle that the inner load of nonlinear synthesis transmission system is difficult to obtain,a new kind of virtual prototype establishment and simulation method is put forward. The influence on nonlinear...Aiming to the puzzle that the inner load of nonlinear synthesis transmission system is difficult to obtain,a new kind of virtual prototype establishment and simulation method is put forward. The influence on nonlinear vibration with flexible rotor, bearing backlash is analyzed based on a virtual prototype. To validate the virtual prototype of nonlinear gear transmission system, the corresponding test platform is established. The consistency between simulation results and test results proves that the simulation results of the virtual prototype can be used to calculate the fatigue reliability life of key components. A new kind of fatigue reliability life prediction method of gear system considering multi-random parameter distribution is put forward based on the fatiguestatistic theory. Considering the periodicity of gear meshing, linear interpolation method is adopted to obtain the stress-time course of random load spectrum based on the gear's complicated torque provided by virtual prototype.The gear's P-Sa-Sm-N curved cluster can be simulated based on material's P-S-N curve. The simulation process considers the parameter distributions of stress concentration coefficients, dimension coefficients and surface quality treatment coefficients, and settles the puzzle that traditional test methods cannot acquire the gear's fatigue life of all reliability levels. This method can provide the distribution function and the interval of fatigue reliability life of gear's danger region, and has a guide meaning for the gear maintenance periods determination and reliability evaluation.展开更多
This article presented a new data fusion approach for reasonably predicting dynamic serviceability reliability of the long-span bridge girder.Firstly,multivariate Bayesian dynamic linear model(MBDLM)considering dynami...This article presented a new data fusion approach for reasonably predicting dynamic serviceability reliability of the long-span bridge girder.Firstly,multivariate Bayesian dynamic linear model(MBDLM)considering dynamic correlation among the multiple variables is provided to predict dynamic extreme deflections;secondly,with the proposed MBDLM,the dynamic correlation coefficients between any two performance functions can be predicted;finally,based on MBDLM and Gaussian copula technique,a new data fusion method is given to predict the serviceability reliability of the long-span bridge girder,and the monitoring extreme deflection data from an actual bridge is provided to illustrated the feasibility and application of the proposed method.展开更多
基金Supported by the National Basic Research Program of China (Grant Nos. 2009CB320602, 2010CB731800)the National Natural Science Foundation of China (Grant Nos. 60721003, 60736026)
文摘As an important technology for predictive maintenance, failure prognosis has attracted more and more attentions in recent years. Real-time reliability prediction is one effective solution to failure prognosis. Considering a dynamic system that is composed of normal, deteriorating and unreliable components, this paper proposes an integrated approach to perform real-time reliability prediction for such a class of systems. For a deteriorating component, the degradation is modeled by a time-varying fault process which is a linear or approximately linear function of time. The behavior of an unreliable component is described by a random variable which has two possible values corresponding to the operating and malfunction conditions of this component. The whole proposed approach contains three algorithms. A modified interacting multiple model particle filter is adopted to estimate the dynamic system＇s state variables and the unmeasurable time-varying fault. An exponential smoothing algorithm named the Holt＇s method is used to predict the fault process. In the end, the system＇s reliability is predicted in real time by use of the Monte Carlo strategy. The proposed approach can effectively predict the impending failure of a dynamic system, which is verified by computer simulations based on a three-vessel water tank system.
基金supported by the Fundamental Research Funds for the Central Universities(2016083)
文摘A useful life prediction method based on the integration of the stochastic hybrid automata(SHA) model and the frame of the dynamic fault tree(DFT) is proposed. The SHA model can incorporate the orbit environment, work modes, system configuration, dynamic probabilities and degeneration of components,as well as spacecraft dynamics and kinematics. By introducing the frame of DFT, the system is classified into several layers, and the problem of state combination explosion is artfully overcome.An improved dynamic reliability model(DRM) based on the Nelson hypothesis is investigated to improve the defect of cumulative failure probability(CFP), which is used to address the failure probability of components in the SHA model. The simulation using the Monte-Carlo method is finally conducted on two satellites, which are deployed with the same multi-gyro subsystem but run on different orbits. The results show that the predicted useful life of the attitude control system(ACS) with consideration of abrupt failure,degradation, and running environment is quite different between the two satellites.
文摘Aiming to the puzzle that the inner load of nonlinear synthesis transmission system is difficult to obtain,a new kind of virtual prototype establishment and simulation method is put forward. The influence on nonlinear vibration with flexible rotor, bearing backlash is analyzed based on a virtual prototype. To validate the virtual prototype of nonlinear gear transmission system, the corresponding test platform is established. The consistency between simulation results and test results proves that the simulation results of the virtual prototype can be used to calculate the fatigue reliability life of key components. A new kind of fatigue reliability life prediction method of gear system considering multi-random parameter distribution is put forward based on the fatiguestatistic theory. Considering the periodicity of gear meshing, linear interpolation method is adopted to obtain the stress-time course of random load spectrum based on the gear's complicated torque provided by virtual prototype.The gear's P-Sa-Sm-N curved cluster can be simulated based on material's P-S-N curve. The simulation process considers the parameter distributions of stress concentration coefficients, dimension coefficients and surface quality treatment coefficients, and settles the puzzle that traditional test methods cannot acquire the gear's fatigue life of all reliability levels. This method can provide the distribution function and the interval of fatigue reliability life of gear's danger region, and has a guide meaning for the gear maintenance periods determination and reliability evaluation.
基金This work was supported by Natural Science Foundation of Gansu Province of China(20JR10RA625,20JR10RA623)National Key Research and Development Project of China(Project No.2019YFC1511005)+1 种基金Fundamental Research Funds for the Central Universities(Grant No.lzujbky-2020-55)National Natural Science Foundation of China(Grant No.51608243).
文摘This article presented a new data fusion approach for reasonably predicting dynamic serviceability reliability of the long-span bridge girder.Firstly,multivariate Bayesian dynamic linear model(MBDLM)considering dynamic correlation among the multiple variables is provided to predict dynamic extreme deflections;secondly,with the proposed MBDLM,the dynamic correlation coefficients between any two performance functions can be predicted;finally,based on MBDLM and Gaussian copula technique,a new data fusion method is given to predict the serviceability reliability of the long-span bridge girder,and the monitoring extreme deflection data from an actual bridge is provided to illustrated the feasibility and application of the proposed method.
