Reliability Assessment Of Complex Electromechanical Systems Based On Performance Degradation

With the progress and development of science and technology,complex electromechanical systems gradually present the characteristics of complex structure,long life,high reliability,and complex failure modes.At the same time,due to the consideration of the economic cost and time cost of the life test,it is difficult for us to obtain a large amount of failure data of complex electromechanical systems.Therefore,the traditional reliability assessment method based on a large amount of failure data faces the problems of small failure data samples and complex failure correlations when evaluating the reliability of complex electromechanical systems.Compared to failure data,it is easier to obtain degradation data that can reflect system performance by adopting sensors during the test or mission phase.Thus,the performance degradation data can reflect the complete process of system failure more directly,fit the failure mechanism of the system,and have a correlation with the system life.Therefore,we consider the pseudo-failure data derived from the degradation data of complex electromechanical systems to present small sample characteristics,and there is competition between multiple performance degradation failures and sudden failures in the failure process,and the reliability evaluation method for complex electromechanical systems based on performance degradation is carried out.Research.In this thesis,complex electromechanical systems are taken as the research object,and their reliability is considered and evaluated from the perspective of performance degradation.First of all,the Bootstrap method is improved and applied to solve the problem of insufficient accuracy of reliability evaluation caused by the small sample of pseudo-life data.Secondly,considering the randomness,individual difference and multivariate degradation correlation in the process of system degradation,the stochastic process model and Copula function are used to model the performance degradation process,and the reliability model of system multivariate correlation performance degradation is introduced.Next,taking the sudden failure into consideration,the proportional hazard model is used to describe the impact of the degradation process on the sudden failure process,and the sudden failure process is modeled,and a multivariate performance degradation system reliability model under competing failures is introduced.The specific work is as follows.First,the thesis proposes a reliability assessment method based on the improved Bootstrap method and the degradation trajectory model.After the system failure analysis determines the failure criteria of the system,and then determines the amount of degradation of the system,an appropriate degradation trajectory model is selected to describe the degradation process of the system according to the degree of quality of the fitting model of the degradation data.The failure threshold of the degradation quantity is determined,and the pseudo-life data of the system is deduced in combination with the degradation trajectory model.Then,the improved Bootstrap method is used to expand the sample of pseudo-lifetime data,including using B-spline function to replace the median rank function as the empirical distribution function for sampling,and using the K-means method to perform cluster analysis on the self-service samples and eliminate some influences on reliability.Self-service sample points for evaluating accuracy.In order to make full use of the pseudo-life data,the Bayesian method is used to estimate the life distribution parameters of complex electromechanical systems,and the lognormal distribution is used to fit the parameter estimates as the prior distribution of the parameter estimates,and use Markov Monte Carlo method to solves for the posterior distribution of the parameters.Finally,the validity of the evaluation method and the accuracy of the evaluation results are verified through the numerical example analysis,and the applicability of the method is also verified through the case analysis of the CNC machine tool electric spindle system.Secondly,in order to fit the actual process of degradation failure of complex electromechanical systems,we evaluate the reliability of complex electromechanical systems considering multiple degradation failures,individual differences of the system and randomness of the system degradation process.After determining the multivariate degradation quantities describing the complex electromechanical system,and according to the characteristics of the data of different degradation quantities,select different nonlinear stochastic process models considering individual differences to model the system degradation process.The correlation of multiple degradation failures is described by selecting an appropriate Copula function through the AIC criterion,and the reliability function of the complex electromechanical system under the correlation of multiple performance degradation failures is derived.Again,the model parameters are solved by the Markov Monte Carlo method.we through the example of aero-engine verification and comparison with the independent case of binary performance degradation failure,it is verified that the reliability evaluation results using the method in this chapter are more suitable for the real reliability of complex electromechanical systems.Finally,in order to further improve the accuracy of reliability evaluation,we consider the sudden failure and evaluates the reliability of complex electromechanical systems from the perspective of competing failures.The thesis proposes a reliability evaluation process that considers multiple performance degradation failures and sudden failures to compete with failures.After the system sudden failure process is modeled,the impact of system performance degradation on the sudden failure process is analyzed,and the proportional hazard model is used to describe it.And the reliability model of the complex electromechanical system under the competition of multiple performance degradation failures and sudden failures is derived.Then,the Markov Monte Carlo method is used to estimate the model parameters.We taking the aero-engine as an example,it is compared with the methods in Chapter 4 that do not consider the sudden failure and other scholars consider the sudden failure,which verifies the accuracy of the evaluation results of the thesis method and is more suitable for the actual situation.