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.
Authors
- Fan Zhang (ORCID: https://orcid.org/0000-0003-4165-8506)
- Wei Cong (ORCID: https://orcid.org/0000-0003-3876-4762)
- Peng Wang (ORCID: https://orcid.org/0000-0002-8738-0602)
Institutions
- Civil Aviation University of China (CN)
Publication Details
- 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
Funders
- Joint Fund of Civil Aviation Research
- National Key Research and Development Program of China