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基于Gamma过程的机车车轮镟修里程预测方法.

Authors :
张义民
林禄样
吕昊
Source :
Journal of Northeastern University (Natural Science). 2018, Vol. 39 Issue 4, p522-526. 5p.
Publication Year :
2018

Abstract

According to measured wheel wear data, the nonstationary Gamma process was used to establish the degradation model of locomotive wheel rim, and the repair time of 95% reliability was predicted by using the two methods a and b combined with wheel rim wear threshold. Method a uses the Bootstrap method to randomly generate a set of empirical distributions of pseudo-life, with Weibull distribution fitting forecasting repair time of 473900km. Method b uses the secondary fourth-order moment method based on the maximum entropy to predict the repair time of 488900km. The results showed that the lifetime of method a is more conservative than that of the empirical method, and the failure distribution of method b is more consistent with that of the experience distribution, and the repair time is 450000km. [ABSTRACT FROM AUTHOR]

Details

Language :
Chinese
ISSN :
10053026
Volume :
39
Issue :
4
Database :
Academic Search Index
Journal :
Journal of Northeastern University (Natural Science)
Publication Type :
Academic Journal
Accession number :
129244887
Full Text :
https://doi.org/10.12068/j.issn.1005-3026.2018.04.014