SVR Prediction Algorithm for Crack Propagation of Aviation Aluminum Alloy
Aluminum alloy material is an important component material in the safe flight of aircraft. It is very important and necessary to predict the fatigue crack growth between holes of aviation aluminum alloy materials. At present, the investigation on the prediction of the cracks between two holes and mu...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2020/1034639 |
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| _version_ | 1832561173029978112 |
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| author | Jincai Chang Zhihang Wang Qingyu Zhu Zhao Wang |
| author_facet | Jincai Chang Zhihang Wang Qingyu Zhu Zhao Wang |
| author_sort | Jincai Chang |
| collection | DOAJ |
| description | Aluminum alloy material is an important component material in the safe flight of aircraft. It is very important and necessary to predict the fatigue crack growth between holes of aviation aluminum alloy materials. At present, the investigation on the prediction of the cracks between two holes and multiholes is a key problem to be solved. Due to the fact that the fatigue crack growth test of aluminum alloy plate with two or three holes was carried out by the MTS fatigue testing machine, the crack length growth data under different test conditions were obtained. In this paper, support vector regression (SVR) was used to fit the crack data, and the parameters of SVR are optimized by the grid search algorithm at the same time. And then the model of SVR to predict the crack length was established. Discussion on the results shows that the prediction model is effective. Furthermore, the crack growth between three holes was predicted accurately through the model of the crack law between two holes under the same load form. |
| format | Article |
| id | doaj-art-bb4ae2cbb68f4b49b89eacf6c50ea584 |
| institution | Kabale University |
| issn | 2314-4629 2314-4785 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj-art-bb4ae2cbb68f4b49b89eacf6c50ea5842025-02-03T01:25:46ZengWileyJournal of Mathematics2314-46292314-47852020-01-01202010.1155/2020/10346391034639SVR Prediction Algorithm for Crack Propagation of Aviation Aluminum AlloyJincai Chang0Zhihang Wang1Qingyu Zhu2Zhao Wang3College of Science, North China University of Science and Technology, Tangshan, Hebei 063210, ChinaCollege of Science, North China University of Science and Technology, Tangshan, Hebei 063210, ChinaAvic China Aero-Polytechnology Establishment, Beijing 100028, ChinaCollege of Science, North China University of Science and Technology, Tangshan, Hebei 063210, ChinaAluminum alloy material is an important component material in the safe flight of aircraft. It is very important and necessary to predict the fatigue crack growth between holes of aviation aluminum alloy materials. At present, the investigation on the prediction of the cracks between two holes and multiholes is a key problem to be solved. Due to the fact that the fatigue crack growth test of aluminum alloy plate with two or three holes was carried out by the MTS fatigue testing machine, the crack length growth data under different test conditions were obtained. In this paper, support vector regression (SVR) was used to fit the crack data, and the parameters of SVR are optimized by the grid search algorithm at the same time. And then the model of SVR to predict the crack length was established. Discussion on the results shows that the prediction model is effective. Furthermore, the crack growth between three holes was predicted accurately through the model of the crack law between two holes under the same load form.http://dx.doi.org/10.1155/2020/1034639 |
| spellingShingle | Jincai Chang Zhihang Wang Qingyu Zhu Zhao Wang SVR Prediction Algorithm for Crack Propagation of Aviation Aluminum Alloy Journal of Mathematics |
| title | SVR Prediction Algorithm for Crack Propagation of Aviation Aluminum Alloy |
| title_full | SVR Prediction Algorithm for Crack Propagation of Aviation Aluminum Alloy |
| title_fullStr | SVR Prediction Algorithm for Crack Propagation of Aviation Aluminum Alloy |
| title_full_unstemmed | SVR Prediction Algorithm for Crack Propagation of Aviation Aluminum Alloy |
| title_short | SVR Prediction Algorithm for Crack Propagation of Aviation Aluminum Alloy |
| title_sort | svr prediction algorithm for crack propagation of aviation aluminum alloy |
| url | http://dx.doi.org/10.1155/2020/1034639 |
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