基于蚁狮优化算法与迹稀疏正则化的结构损伤识别  

Structural damage detection based on an ant lion optimizer algorithm and trace sparse regularization

作　　者：陈承滨 余岭 潘楚东[1] 陈泽鹏 CHEN Chengbin;YU Ling;PAN Chudong;CHEN Zepeng(School of Mechanics and Construction Engineering,Jinan University,Guangzhou 510632,China;MOE Key Lab of Disaster Forecast and Control in Engineering,Jinan University,Guangzhou 510632,China)

机构地区：[1]暨南大学力学与建筑工程学院,广州510632 [2]暨南大学重大工程灾害与控制教育部重点实验室,广州510632

出　　处：《振动与冲击》2019年第16期71-76,99,共7页Journal of Vibration and Shock

基　　金：国家自然科学基金(51678278;51278226)

摘　　要：针对基于群智能结构损伤识别既有方法的识别精度和抗噪鲁棒性不足问题,提出基于蚁狮优化算法与迹稀疏正则化的方法求解结构损伤识别问题。将结构损伤识别逆问题转化为数学中的约束优化问题,并根据模型修正原理利用结构模态参数定义优化问题的目标函数;在目标函数中引入迹稀疏约束;通过不同损伤工况下简支梁损伤识别数值模拟以及钢管简支梁实验验证方法的有效性。结果表明,基于蚁狮优化算法与迹稀疏正则化的结构损伤识别法能有效修正有限元模型,在不同噪声水平和损伤工况下不仅能准确定位损伤位置,且能精确识别损伤程度;该方法为结构损伤的现场识别提供了可能性。Classical swarm intelligence(SI)based structural damage detection(SDD)methods have some common deficiencies,such as low identified accuracy and low robustness.In order to solve the above problems,a novel method based on the ant lion optimizer(ALO)algorithm and trace sparse regularization was proposed to solve the SDD problem.First of all,the SDD inverse problem was transformed into a constrained optimization problem in mathematics.According to the model updating principle,the objective function of the SDD optimization problem was defined by the structural modal parameters.Then,the trace sparse constraint was introduced into the objective function.Finally,the validity of the proposed method was verified by numerical simulations of a simply-supported beam in damage patterns and by measurement data of a steel-tube simply-supported beam.The SDD results show that the proposed SDD method can effectively update the finite element model(FEM).Under different noise levels and damage patterns,the proposed method can accurately locate damages and quantify damage severities.

关 键 词：结构损伤识别(SDD) 蚁狮优化算法(ALO) 迹稀疏正则化 约束优化问题 模型修正 

分 类 号：O327[理学—一般力学与力学基础] TU311[理学—力学]