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Structural sparse damage identification considering ambient temperature variations based on support vector machine and enhanced moth-flame optimization

DOI：10.7511/jslx20210302002

 作者 单位 E-mail 雷勇志 武汉工程大学 土木工程与建筑学院, 武汉 430074 黄民水 武汉工程大学 土木工程与建筑学院, 武汉 430074 顾箭峰 武汉工程大学 土木工程与建筑学院, 武汉 430074 gjfcqucdu@wit.edu.cn 杨雨厚 广西交科集团有限公司, 南宁 530007 舒国明 河北交通职业技术学院, 路桥工程系, 石家庄 050035

结构处于自然环境中常会受到环境温度变化的影响,引起实测动力响应出现较大误差,进一步影响对结构健康状况的判定。另外,基于优化算法的损伤识别在反演损伤位置及量化损伤程度时,易出现局部最优解,且计算效率低下。针对以上难题,本文提出一种结合支持向量机与强化飞蛾扑火优化算法的损伤识别方法,用于对环境温度影响下的结构稀疏损伤进行识别。该方法首先采取支持向量机对环境温度变化进行量化分析;随后引入稀疏正则化确定稀疏损伤工况;接着将获得的环境温度变化及损伤工况信息作为强化飞蛾扑火优化算法的初始种群生成依据,从而得到针对实际损伤的初始种群用于缩小算法搜索空间,提高计算效率。最后采用基于频率的结构多损伤定位保证准则及模态应变能基本因子构建目标函数,通过考虑环境温度及随机噪声双重影响的简支梁数值算例以及I-40钢-混组合体系桥梁工程实例验证了本文所提方法的可行性。

Civil engineering structures are always affected by ambient temperature variations,which will influence the results of modal testing and set up obstacles to the evaluation of real structural damage.Furthermore,a damage identification method based on an optimization algorithm is easy to be trapped in a local optimum and lower computing efficiency when the method is used to locate and quantify damage.Aiming to the above problems,in this paper,a damage identification method,which is based on support vector machine (SVM) and enhanced moth-flame optimization (EMFO),is proposed to solve a structural sparse damage identification problem considering temperature variations.Firstly,SVM is used to quantify structural temperature variations.Then,a sparse regularization method is introduced to determine structural sparse damage conditions.Thirdly,the temperature variations and damage situation obtained in the previous step are adopted to perform the initialization of EMFO,which can narrow the search space,and enhance damage identification efficiency.Finally,two examples,a simulated simply supported beam considering temperature variations and random noise effects,and a real engineering structure of I-40 Bridge,a large steel-concrete composite bridge,are utilized to verify the effectiveness of the proposed method.