Bayes feature fusion reliability evaluation model based on data migration

被引：0
|
作者：
Zhang X. [1 ,2 ]
Tang J. [1 ,2 ]
Tang L. [1 ]
机构：
[1] School of Mathematics, Southwest Jiaotong University, Chengdu
[2] National Engineering Laboratory of Comprehensive Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu
来源：
Hangkong Dongli Xuebao/Journal of Aerospace Power | 2024年 / 39卷 / 03期
关键词：
Bayesian; data fusion; data migration; exponential distribution; reliability;
D O I：
10.13224/j.cnki.jasp.20210558
中图分类号：
学科分类号：
摘要：
Based on the life data information from multiple test sources， using the mapping relationship between different data sources，the multi-source data were migrated to the field data source to form a mixed data source， which was used as the basis for the Bayesian statistical analysis of product reliability. For the accelerated life data under different stresses，it was converted to the constant stress level to determine the parameter distribution density function， which was used as the priori condition for the product reliability Bayesian statistical analysis. By combining the Bayesian statistical model with the data migration model，and fusing multi-source data while determining the parameter estimates at the same time，the product density function and the product reliability analysis were obtained. The example showed that this model can effectively achieve data migration by utilizing the mapping relationship between data sources， and can accelerate the synchronous fusion of life data with other types of data sources. The comprehensive evaluation of product reliability after fusing sample data was more comprehensive and objective than that of a single life data source. © 2024 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.
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