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您的检索式：作者名="DAI Hongde"
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| 1 | Remaining useful life prediction based on variation coefficient consistency test of a Wiener process显示文摘High-cost equipment is often reused after maintenance, and whether the information before the maintenance can be used for the Remaining Useful Life(RUL) prediction after the maintenance is directly determined by the consistency of the degradation pattern before and after the maintenance.Aiming at this problem, an RUL prediction method based on the consistency test of a Wiener process is proposed.Firstly, the parameters of the Wiener process estimated by Maximum Likelihood Estimation(MLE) are proved to be biased, and a modified unbiased estimation method is proposed and verified by derivation and simulations.Then, the h statistic is constructed according to the reciprocal of the variation coefficient of the Wiener process, and the sampling distribution is derived.Meanwhile, a universal method for the consistency test is proposed based on the sampling distribution theorem, which is verified by simulation data and classical crack degradation data.Finally, based on the consistency test of the degradation model, a weighted fusion RUL prediction method is presented for the fuel pump of an airplane, and the validity of the presented method is verified by accurate computation results of real data, which provides a theoretical and practical guidance for engineers to predict the RUL of equipment after maintenance. | Juan LI Bo JING Hongde DAI Xiaoxuan JIAO Xiaodong LIU | 2018 | Chinese Journal of Aeronautics2018，31，1： | 5 |
| 2 | A New Dynamic-Copula Based Correlated Degradation Feature for Remaining Useful Life Prediction显示文摘Feature extraction plays an important role in Remaining useful life(RUL)prediction.Feature extraction mainly depends on the performance degradation signal in the previous study,in which the dynamic correlations among different signals are ignored,and the RUL accuracy is affected.A new dynamic feature based on the correlations of the performance degradation signal is proposed.First,dynamic correlation coefficients are calculated by copula function as the multivariate correlation performance degradation features.Second,the random effect Wiener process is used for RUL prediction based on the new features,and the maximum likelihood estimation is adopted to calculate the unknown parameters of the Wiener process.Finally,the RUL estimation for solder joints under vibration load is carried out compared with the quantile and quantile-Principal component analysis(PCA)mixed feature extraction method.The research results show that the proposed method improved the prediction accuracy of RUL. | LI Juan DAI Hongde JING Bo JIAO Xiaoxuan | 2021 | Chinese Journal of Electronics2021，30，1： | 0 |
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