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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

DOI：10.7511/jslx20221124003

 作者 单位 E-mail 陈泽鹏 佛山科学技术学院 交通与土木建筑学院, 佛山 528225暨南大学 重大工程灾害与控制教育部重点实验室, 广州 510632 zpchen2014@foxmail.com 王伟龙 佛山科学技术学院 交通与土木建筑学院, 佛山 528225 刘琪钿 佛山科学技术学院 交通与土木建筑学院, 佛山 528225 吴京涛 佛山科学技术学院 交通与土木建筑学院, 佛山 528225

受算法随机参数和测量噪声等因素的影响,基于群智能算法的结构损伤识别法容易出现单次识别误差大和多次识别波动大的问题。针对该问题,本文基于混合PSO算法和损伤概率均值提出一种两阶段梁式结构损伤识别方法。定义了包括单元容许损伤值αcr和临界概率pc的损伤有效原则,以计算损伤概率均值。第一阶段,对混合PSO算法的多次识别结果分批计算一阶段损伤概率均值,第二阶段,在此基础计算两阶段损伤概率均值。本文方法能够有效地提高高噪声水平影响下的结构损伤识别精度。简支梁和两跨连续梁的损伤工况试验研究表明,该算法能够有效地应用于不同结构和不同工况的结构损伤识别,在减少损伤误判的同时保证损伤单元的识别精度。

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.