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| Bayes Fusion Evaluation Method for Storage Data of Composite Inspection with Fuzzy Samples |
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| DOI：10.7643/issn.1672-9242.2023.05.009 |
| KeyWord:composite inspection ex-factory failure fuzzy samples Bayes fusion weighted least square method based on sample size storage life evaluation |
| Author | Institution |
| YE Ke-wei |
School of Reliability and Systems Engineering, Beihang University, Beijing , China |
| WANG Han |
School of Reliability and Systems Engineering, Beihang University, Beijing , China |
| MA Xiao-bing |
School of Reliability and Systems Engineering, Beihang University, Beijing , China |
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| Abstract: |
| The work aims to evaluate the storage life of composite inspection products with fuzzy samples. The compatibility test was carried out on the ex-factory failure data and storage failure data of batch products. The uncertainty of fuzzy samples in the storage process was quantified by randomizing the number of ex-factory failure samples. With the failure data in the ex-factory inspection as prior information and the ex-factory failure data in the storage inspection as observation information, the ex-factory failure probability was updated based on Bayes fusion method. The composition of fuzzy samples was determined by the updated ex-factory failure probability, and the storage failure samples were screened out. The storage life of the products was evaluated based on the screened storage failure probability by the weighted least square method. The proposed method was applied to a missile product case. The ex-factory failure probability and its estimation variance were accurately estimated and the reliable life evaluation results were given. The proposed Bayes fusion method combines the ex-factory inspection data and the storage inspection data and effectively solves the failure probability estimation problem containing fuzzy samples and improves the estimation accuracy. The weighted least square method based on sample size considers the reliability of samples, which is more scientific. |
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