Comparative studies on structural damage detection using Lp norm regularisation. (25th June 2019)

• Record Type: Journal Article
• Authors: Yue, Zhenguang; Chen, Zepeng; Yu, Ling
• Is Part Of: International journal of lifecycle performance engineering. Volume 3:Number 2(2019)
• Page Start: 171
• Page End: 186
• Publication Date: 2019-06-25
• Subjects: structural health monitoring -- SHM -- structural damage detection -- SDD -- damage factor vector -- model updating technique -- frequency -- mode shape -- optimisation problem -- sensitivity analysis -- Lp (0 < p < 1) norm regularisation -- sparse regularisation; Structural analysis (Engineering) -- Periodicals; Buildings -- Performance -- Periodicals; 624.1705
• Languages: English
• ISSNs: 2043-8648

Abstract

In order to get sparse solution to the structural damage detection (SDD) problem, a new SDD method is proposed based on the finite element model updating technique through combining sensitivity analysis with the L p (0 < p < 1) norm regularisation. Compared with the classical Tikhonov regularisation, the L p norm regularisation method can avoid over-smoothness, which is a main difficulty for the Tikhonov regularisation, and its solutions are also more accurate than that by the L 1 norm regularisation, another widely used sparse regularisation method. Moreover, the effects of different p -values on SDD results are also studied and discussed. Numerical simulations on a cantilever beam and a simple supported beam, and all the laboratory experiments on a cantilever beam under different assumed damage cases verify the effectiveness of the proposed method. The SDD results show that a good sparse solution is assured via the L p norm regularisation especially when the value of p ranges from 0.1 to 0.5. In contrast, its accuracy shows a slightly decline when the value of p changes from 0.5 to 1.0. Finally, the results also show that p = 1/2 is the best choice for SDD when using L p norm regularisation.