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| A two-stage structural damage detection method for beam-like structures based on hybrid PSO and probabilistic mean of damage vector factor |
| Received:November 24, 2022 Revised:April 24, 2023 |
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| DOI：10.7511/jslx20221124003 |
| KeyWord:structural damage detection hybrid PSO algorithm effective damage principle probabilistic mean of damage vector factor beam-like structures |
| Author | Institution |
| 陈泽鹏 |
佛山科学技术学院 交通与土木建筑学院, 佛山 ;暨南大学 重大工程灾害与控制教育部重点实验室, 广州 |
| 王伟龙 |
佛山科学技术学院 交通与土木建筑学院, 佛山 |
| 刘琪钿 |
佛山科学技术学院 交通与土木建筑学院, 佛山 |
| 吴京涛 |
佛山科学技术学院 交通与土木建筑学院, 佛山 |
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| Abstract: |
| Due to the random parameters of algorithms and measurement noise,structural damage detection methods based on swarm intelligence algorithms are prone to large errors in single identification and large fluctuation in multiple identification.Therefore,this paper proposes a two-stage a damage detection method for beam structures based on a hybrid PSO algorithm and the probabilistic mean of a damage vector factor.An effective damage principle is defined including an elemental allowable damage value αcr and two critical probability parameters pc1 and pc2. In the first stage,multiple SDD results based on the hybrid PSO are divided into several batches and the corresponding probabilistic means of the damage vector factor are calculated as the first stage probabilistic means.Then,a new probabilistic means of the damage vector factor is determined as the final SDD results based on the results in the first stage.The proposed method can effectively improve the accuracy of structural damage detection under the influence of high noise.Numerical studies on damage cases of a simply-supported beam and a two-span continuous beam demonstrate the effectiveness and efficiency of the proposed method. |