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| Prediction of Storage Life Based on Genetic BP Algorithm |
| Received:June 13, 2024 Revised:July 13, 2024 |
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| DOI：10.7643/issn.1672-9242.2024.08.005 |
| KeyWord:step test BP neural network genetic algorithm constant humidity step temperature environmental factor Arrhenius model |
| Author | Institution |
| GUO Junling |
School of Mechanical and Electrical Engineering, North University of China, Taiyuan , China |
| PENG Zhiling |
School of Mechanical and Electrical Engineering, North University of China, Taiyuan , China |
| BAN Wei |
Yichang Testing Technology Research Institute, Hubei Yichang , China |
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| Abstract: |
| In order to solve the problem of large amount of calculation and long test time in the statistical method of fuze natural storage test data, the work aims to propose a method combining BP and genetic algorithm (genetic BP algorithm), so as to solve the life prediction problem through step test. Firstly, the environmental factors under various levels of stress were calculated through step test data. The environmental factors were used to convert the stress test time at each level into the actual storage time, and the reliability function was calculated based on the model. Secondly, genetic algorithm was used to optimize the BP neural network to avoid the local optimal problem of BP. The step test data were substituted into the genetic BP algorithm for training, to improve the accuracy and precision of prediction. The data under normal stress were substituted into the genetic BP algorithm for testing, and the predicted reliability value was calculated. Finally, the actual storage reliability value and the predicted storage reliability values of model, and genetic BP algorithm were compared, which were similar, proving that the genetic BP algorithm could meet the prediction of fuze storage reliability. The genetic BP algorithm for predicting the lifespan of step test can effectively reduce the test duration and lower the test cost. |
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