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基于遗传算法的高速铁路桥梁损伤识别

Damage identification of high-speed railway bridge based on genetic algorithm

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针对高速铁路桥梁结构服役局部损伤问题,文章提出一种改进损伤识别因子并结合遗传算法的损伤识别方法.推导了任意单元长度组合的车辆-轨道-桥梁耦合单元及其动力方程,遗传算法采用锦标赛策略及最优保存策略2种选择算子,引入灾变及邻域搜索机制.通过对不同损伤工况进行多次独立重复计算,对算法的稳定性与准确性进行统计分析.结果表明:在信噪比(signal-to-noise ratio,SNR)大于25 dB时,识别效果好,极少数误判的结果大概率存在于真实损伤位置的附近或对称处;与单个单元损伤情况相比,多个单元损伤工况平均第一次出现最优解的迭代次数略高,但整体都偏低;SNR与识别率(identification rate,IR)呈"扁S"型Logistic曲线关系.
Aiming at the problem of local damage in service of high-speed railway bridge structure,this paper proposes a damage identification method based on improved damage identification factor and ge-netic algorithm.The train-rail-bridge coupling element and its dynamic equation of arbitrary element length combination are derived.The genetic algorithm adopts two selection operators,tournament strategy and optimal preservation strategy,and introduces disaster and neighborhood search mecha-nism.The stability and accuracy of the algorithm are analyzed statistically by repeated calculation of different damage conditions.The results show that when the signal-to-noise ratio(SNR)is greater than 25 dB,the identification effect is good,and a small number of misjudgments have a high proba-bility of being near or symmetric to the real damage location.Compared with the damage condition of a single unit,the average number of iterations of the first optimal solution in multi-unit damage condi-tions is slightly higher,but the overall number is lower.SNR and identification rate(IR)form a flat S-shaped Logistic curve relationship.

train-rail-bridge coupling systemdynamic responsedamage identificationgenetic algo-rithmwhite Gaussian noise

杨宏印、张威、曹鸿猷、吴楠昊、刘章军

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武汉工程大学土木工程与建筑学院,湖北武汉 430073

桥梁结构健康与安全国家重点实验室,湖北武汉 430034

武汉理工大学土木工程与建筑学院,湖北武汉 430070

车辆-轨道-桥梁耦合系统 动力响应 损伤识别 遗传算法 高斯白噪声

国家自然科学基金资助项目湖北省高等学校优秀中青年科技创新团队计划资助项目武汉市城乡建设局科技计划资助项目武汉工程大学第十三届研究生教育创新基金资助项目桥梁结构健康与安全国家重点实验室开放课题资助项目

51708429T2020010201919CX20211202017-04-GF

2024

10.3969/j.issn.1003-5060.2024.07.010

合肥工业大学学报(自然科学版)
合肥工业大学

合肥工业大学学报(自然科学版)

CSTPCD北大核心
影响因子：0.608
ISSN：1003-5060
年,卷(期)：2024.47(7)