Multi-source data fusion and reliability analysis based on TPAC-KL model

With the increasing life span of aviation products, product reliability data is difficult to obtain and there are challenges in reliability analysis. In this regard, this paper proposes a multi-source data fusion method based on the TPAC-KL model. Firstly, under the two-parameter Weibull distribution model, the Maximum Likelihood Estimation of multi-source data is carried out to obtain the characteristics life of each type of data source; secondly, the TPAC Attribute Method is proposed to measure the credibility of the data sources, and the average similarity of the data sources is measured by the KL divergence; finally, the fusion of multi-source data is realized and the reliability analysis is carried out. The results show that the TPAC-KL model can effectively fuse the reliability information from different data sources, balance the differences between multi-source data, and improve the accuracy of the overall prediction of the target product reliability.

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Published
2024-10-23
DOI
https://doi.org/10.1109/iccasit62299.2024.10827920
Primary Topic
Advanced Decision-Making Techniques
Type
article
Field-Weighted Citation Impact
0.00

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Multi-source data fusion and reliability analysis based on TPAC-KL model

Fan Zhang, Wei Cong, Peng Wang
Advanced Decision-Making Techniques
article

Multi-source data fusion and reliability analysis based on TPAC-KL model

Fan Zhang, Wei Cong, Peng Wang
article en

Abstract

With the increasing life span of aviation products, product reliability data is difficult to obtain and there are challenges in reliability analysis. In this regard, this paper proposes a multi-source data fusion method based on the TPAC-KL model. Firstly, under the two-parameter Weibull distribution model, the Maximum Likelihood Estimation of multi-source data is carried out to obtain the characteristics life of each type of data source; secondly, the TPAC Attribute Method is proposed to measure the credibility of the data sources, and the average similarity of the data sources is measured by the KL divergence; finally, the fusion of multi-source data is realized and the reliability analysis is carried out. The results show that the TPAC-KL model can effectively fuse the reliability information from different data sources, balance the differences between multi-source data, and improve the accuracy of the overall prediction of the target product reliability.

Civil Aviation University of China (CN)
Joint Fund of Civil Aviation Research, National Key Research and Development Program of China
Industry, innovation and infrastructure
Openalex Percentile: Top 59%
Advanced Decision-Making Techniques
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Multi-source data fusion and reliability analysis based on TPAC-KL model — Fan Zhang, Wei Cong, et al. · (2024) | TGRS Research Map | TGRS