Research On Reliability Evaluation Method Of Micro-nano Satellite System

Since the concept of micro-nano satellite was put forward,driven by the multidisciplinary development of MEMS technology and highly integrated technology,it has gradually shifted from the early stage of technical verification to the stage of business application.Due to the complexity of the space environment and the particularity of the working conditions,the products on the satellite are not repairable.The reliability analysis of micro-nano satellites is one of the core issues in the field of space research.Micro-nano satellite products have the characteristics of high reliability and long life so that the test cost is very high.It is difficult to obtain sufficient product failure data within the allowable test time.The traditional reliability evaluation methods are based on statistical analysis methods in the case of large samples.However,traditional methods will bring large deviations on dealing with the small sample problems.The failure data of satellite products often come from multiple sources,including actual degradation data,life data and performance degradation data of similar products.This thesis focuses on performance degradation data to study the reliability evaluation technology of micro-nano satellite products.The main research contents are as follows:(1)Reliability assessment method of degradation trajectory and degradation distribution.First,this thesis analyzes the characteristics of performance degradation data and introduces two methods of processing degradation data based on statistical analysis methods.Then,the relationship between product performance degradation trajectory and degradation distribution and time is analyzed.The method of replacing right censored data with pseudo-failure life data is discussed.The detailed steps for reliability evaluation based on degradation trajectory and degradation distribution are given.Finally,these two methods are used to evaluate the reliability of the onboard fiber optic gyroscope,which verifies the effectiveness and simplicity of the proposed method.(2)Reliability evaluation method of stochastic process.First,this thesis introduces the definitions of the three processes: the Wiener process without considering individual differences,the Gamma process,and the Wiener process considering individual differences.Then,three methods for estimating the parameters in the performance degradation model are given,including Markov Chain Monte Carlo(MCMC)method.Finally,three kinds of stochastic process models are used to evaluate the reliability of momentum wheel combined with the performance degradation data.The reliability evaluation results are compared and analyzed to verify that the stochastic process model can effectively deal with the small sample problem of the momentum wheel.(3)Reliability assessment method based on fusion of multi-source information.First,the Wiener process with both drift and diffusion coefficient as random variables is selected for modeling.The performance degradation data and life information of similar products are fused,and in order to obtain the prior distribution of model parameters using the expectation maximization(EM)algorithm at here.Then,the Bayes method is used to fuse the on-site degradation data of the product to continuously update the model parameters to obtain the posterior distribution of the degradation process model parameters.The updated parameters are used to evaluate the reliability of the product.Finally,taking the harmonic gear as an example,the real-time reliability assessment of individual product is realized.Meanwhile,the rationality and accuracy of the proposed method are verified.