Research on structure damage identification method based on point cloud curvature and improved wavelet de-noising function
characteristic curvature of discrete point clouds is also presented in this paper.For the problem that the original signal in the characteristic curvature is seriously disturbed by the point cloud noise,a new wavelet de-noising algorithm based on threshold function is proposed.The method can better identify the original low frequency signal and suppress the abnormal high frequency signal.Finally,the accuracy and sensitivity of the proposed damage identification method based on the characteristic curvature and the improved wavelet threshold de-noising function are verified by full-scale model test.This method has the potential to be applied to structural health monitoring,since it can provide a new technical method for the early warning of the beam structure bridge.
SFM Feature Curvature Wavelet de-noising Threshold function Damage identification
Chu Xi Zhou Zhixiang Luo Dong Jiang Tengjiao Lei Yangkun
Dept.of State Key Laboratory Breeding Base of Mountain Bridge Tunnel Engineering,Chongqing Jiaotong University,Chongqing,400074,China
国际会议
The 7th World Conference on Structural Control and Monitoring(7WCSCM)(第七届结构控制与监测世界大会)
青岛
英文
3276-3280
2018-07-22（万方平台首次上网日期，不代表论文的发表时间）