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| Evaluation Method of Acceleration Factors for the Single-stress Accelerated Test of Old Products Based on the Nonlinear Degradation Model |
| Received:March 28, 2025 Revised:May 15, 2025 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7643/issn.1672-9242.2025.05.003 |
| KeyWord:old products small sample size single stress nonlinear degradation acceleration factor evaluation storage life evaluation |
| Author | Institution |
| XU Ruyuan |
Aerospace Science and Industry Defense Technology Research and Test Center, Beijing , China |
| ZHANG Shengpeng |
Aerospace Science and Industry Defense Technology Research and Test Center, Beijing , China |
| TANG Yubin |
Aerospace Science and Industry Defense Technology Research and Test Center, Beijing , China |
| NI Ruizheng |
Aerospace Science and Industry Defense Technology Research and Test Center, Beijing , China |
| LI Hao |
Aerospace Science and Industry Defense Technology Research and Test Center, Beijing , China |
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| Abstract: |
| To address the problem of difficulty in evaluating the storage life under the scenario of single-stress accelerated storage tests for old products, the work aims to study the evaluation method of the acceleration factors based on the nonlinear degradation model.The natural storage and accelerated storage test data of products were fitted and analyzed with the least squares method based on the nonlinear degradation model, and the ratios of the degradation rates at different stages were calculated. The acceleration factors of the product were evaluated by the ratio of degradation rates at different stages of the nonlinear degradation model, and the results were compared with those of the traditional linear model. The errors of acceleration factors, equivalent storage life of storage test, and extrapolated storage life of storage test were 9.68%, 2.80%, and 10.84%, respectively. This method can effectively solve the problem of evaluating the acceleration factors in single-stress accelerated storage tests for old products, providing support for the accurate assessment of the life of small-sample products. |
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