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| Data Processing Method Based on Arc Model for Accelerated Degradation Testing of Fluorine Rubber Seal Ring |
| Received:May 27, 2024 Revised:July 07, 2024 |
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| DOI：10.7643/issn.1672-9242.2024.08.010 |
| KeyWord:reliability fluorine rubber seal ring accelerated degradation testing arc model storage life life evaluation |
| Author | Institution |
| CAO Zhisheng |
Beijing Aerospace Stone Technology Co., Ltd., Beijing , China;System Design Institute of Mechanical-electrical Engineering, Beijing , China |
| WANG Lin |
PLA Rocket Force |
| TIAN Gang |
Beijing Aerospace Stone Technology Co., Ltd., Beijing , China;System Design Institute of Mechanical-electrical Engineering, Beijing , China |
| LI Yu |
System Design Institute of Mechanical-electrical Engineering, Beijing , China |
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| Abstract: |
| The work aims to evaluate the storage life of fluorine rubber seal rings and solve the problems that is difficult to be determined in evaluation. An arc model was used to analyze the performance of the compression permanent deformation of the fluorine rubber O-ring with φ17.5mm×2.4mm in the process of high temperature accelerated test with accelerated aging time, determine the initial value of the performance parameters of the fluorine rubber seal ring, and transform the performance test data. The binomial data of arc radius and aging time were fitted by the least square method, and the mathematical relation between arc radius and aging time at a certain acceleration temperature was obtained. Then, the velocity constant of any aging time was calculated, and the storage life of the fluorine rubber seal ring under the standard storage temperature was extrapolated based on the Arrhenius model. A high temperature accelerated aging test was designed under 5 stress conditions to obtain performance degradation data and verify the data processing method proposed in this paper. Through the processing of the test data, the longest life of the fluorine rubber seal ring was 32.2 years based on the arc model, and the storage life is closer to the design requirement of 25 years. In conclusion, based on the arc model, regularly degraded data can be analyzed and processed. It avoids the process of solving the empirical multiple approximations in traditional data processing, and has high engineering application value. |
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