L1 regularized model updating for structural damage detection

摘要：

　　The l2 regularized model updating has been widely used to detect structural damage.However,this technique generally results in the identified damage distributed a number of structural elements,which does not represent the actual scenario that the number of damaged elements is small.An l1 regularized model updating based on the sparse recovery theory is developed to detect structural damage.Two different approaches are considered in the present paper,namely,the frequency changes and the combination of frequency changes and mode shape changes.During the model updating process,the measured modal data before and after damage are compared directly and an accurate analytical model is thus not needed.The proposed technique is applied to a cantilever beam.The results show that only the first six modal frequencies and mode shapes are sufficient to detect sparse damaged elements among 100 finite beam elements.

关键词： Damage detection regularization sparse recovery theory vibration data model updating

作者: Yuhan Wu Xiaoqing Zhou Yong Xia

作者单位: College of Civil Engineering,Shenzhen University,Shenzhen,China Department of Civil and Environmental Engineering,The Hong Kong Polytechnic University,Hong Kong,Chi

会议类型: 国际会议

会议名称: The 7th World Conference on Structural Control and Monitoring(7WCSCM)(第七届结构控制与监测世界大会)

会议地点: 青岛

会议语种:英文

页码: 1895-1901

在线出版日期: 2018-07-22（万方平台首次上网日期，不代表论文的发表时间）