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| Structural damage identification based on improved gray wolf optimization algorithm |
| Received:August 22, 2022 Revised:October 02, 2022 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx20220822001 |
| KeyWord:structural damage identification gray wolf algorithm sensitivity location method dynamic characteristic parameters Nelson method |
| Author | Institution |
| 谢少鹏 |
广东工业大学 先进制造学院, 揭阳 |
| 吴柏生 |
广东工业大学 机电工程学院, 广州 |
| 赵秀婷 |
广东工业大学 先进制造学院, 揭阳 |
| 邹敏清 |
广东工业大学 实验教学部, 广州 |
| 林丹锐 |
广东工业大学 先进制造学院, 揭阳 |
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| Abstract: |
| In this paper,a new objective function is constructed to solve the damage identification problem by combining three indicators with good identification accuracy:modal flexibility matrix,generalized modal flexibility matrix and mode shape.The derivative of a frequency and a mode shape obtained by Nelson method is used to obtain the positions that are more sensitive to the change of structural stiffness,and then sensors are arranged at these positions to extract structural information.Although the original gray wolf algorithm has strong global search ability,it has the problem of poor local search accuracy.This paper improves the local search ability and convergence speed of gray wolf algorithm from the aspects of initial population,convergence factor,etc.Finally,the effectiveness of the proposed method is demonstrated by identifying the damage elements in a beam model and a truss model. |
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