| 基于一致性检验的航空发动机剩余寿命预测 |
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| 引用本文： | 黄亮,刘君强,贡英杰. 基于一致性检验的航空发动机剩余寿命预测[J]. 系统工程与电子技术, 2018, 40(12): 2736-2742. DOI: 10.3969/j.issn.1001-506X.2018.12.17 |
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| 作者姓名： | 黄亮 刘君强 贡英杰 |
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| 作者单位： | 南京航空航天大学民航学院, 江苏 南京 211106 |
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| 摘 要： | 针对目前没有将退化的多阶段性和维修前的退化数据用于维修后的剩余寿命预测问题,提出了一种基于多阶段Wiener过程的正态总体均值和变异系数一致性检验的剩余寿命预测方法。首先选用Wiener过程构建多阶段的退化模型;然后根据维修前后的退化监测数据,提出了正态总体均值的一致性检验方法,在检验结果的基础上根据变异系数的倒数构造H随机变量,提出了一种基于概率分布的数据一致性检验方法。最后,根据维修前后的退化数据的一致性检验结果,融合维修前后的退化数据进行剩余寿命的预测,通过预测误差对比结果证实了所提检验方法的有效性。
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Residual lifetime prediction of aeroengines based on the consistency test |
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| HUANG Liang,LIU Junqiang,GONG Yingjie. Residual lifetime prediction of aeroengines based on the consistency test[J]. System Engineering and Electronics, 2018, 40(12): 2736-2742. DOI: 10.3969/j.issn.1001-506X.2018.12.17 |
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| Authors: | HUANG Liang LIU Junqiang GONG Yingjie |
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| Affiliation: | College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China |
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| Abstract: | Aiming at the problem of predicting the residual lifetime after maintenance without considering the multi-stage variability of degradation and the degradation data before maintenance, a method of the prediction of the residual lifetime based on the normal population mean and variation coefficient consistency test of Wiener process is proposed. Firstly, a multi-stage degradation model is established according to the Wiener process. Secondly, according to the degradation monitoring data before and after maintenance, the consistency test of the normal population mean is proposed. Then on the basis of the test results,the H statistic is constructed according to the reciprocal of the variation coefficient,and a method for the consistency test based on probability distribution is proposed. Finally, based on the consistency test results of the degradation data before and after maintenance, the value of the prediction of the residual life is obtained by integrating the data before and after maintenance. The validity of the proposed test method is confirmed by the comparison of prediction errors. |
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