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| Structural damage identification using mayfly intelligent algorithm and static response surface model |
| Received:May 08, 2023 Revised:July 10, 2023 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx20230508001 |
| KeyWord:mayfly algorithm static damage identification Response Surface Model static damage equation static residual |
| Author | Institution |
| 宋彦朋 |
武汉工程大学邮电与信息工程学院, 武汉 |
| 陈辉 |
武汉工程大学邮电与信息工程学院, 武汉 ;武汉理工大学 土木工程与建筑学院, 武汉 |
| 黄斌 |
武汉理工大学 土木工程与建筑学院, 武汉 ;武汉理工大学 海南研究院, 三亚 |
| 吴志峰 |
华中科技大学 土木与水利工程学院, 武汉 |
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| Abstract: |
| This paper presents a structural damage identification method combining the Mayfly Intelligent Search Algorithm and Static Response Surface Model (SRSM).First,a regularized optimization objective function is constructed based on the sensitivity-based static residual damage equation and displacement residual index,and then the Mayfly Intelligent Search Algorithm in the field of artificial intelligence is used to identify the damage at the structural element level.In the optimization process,in order to solve the problem of inconsistency between static load points and displacement measurement points,the static condensation and displacement extension methods are used to reconstruct the damage identification equation.At the same time,the displacement residual in the objective function is calculated by using the static displacement SRSM,which avoids the time-consuming finite element calculation and improves the optimization efficiency.The numerical example of a simply-supported simple beam shows that the proposed method is superior to the traditional Particle Swarm (PSO) or Differential Evolution (DE) algorithms in terms of optimization speed and accuracy;compared with the method based on the static residual damage equation or displacement residual index alone,the damage identification is more accurate.The static-load experiment of an aluminum alloy cantilever beam with damage further verifies the efficiency and effectiveness of the method in this paper. |
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