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Issue title: Selected papers from the International Symposium on Applied Electromagnetics and Mechanics - ISEM 2019
Guest editors: Jinhao Qiu, Ke Xiong and Hongli Ji
Article type: Research Article
Authors: Guan, Weia | Dong, Longleia; | Zhou, Jinxionga
Affiliations: [a] State Key Laboratory for Strength and Vibration of Mechanical Structures, and School of Aerospace Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, China
Correspondence: [*] Corresponding author: Longlei Dong, State Key Laboratory for Strength and Vibration of Mechanical Structures, and School of Aerospace Engineering, Xi’an Jiaotong University, Xi’an 710049, Shaanxi, China. E-mail: dongll@mail.xjtu.edu.cn
Abstract: With the engineering structures becoming more complicated, it is difficult to obtain complete measurement responses with limited sensors. Thus, carrying out the underdetermined modal identification will have practical engineering application values. In this paper, a new approach for underdetermined blind modal identification based on dictionary learning in the framework of compressed sensing (CS) is proposed. The principal idea is to estimate modal shapes using a clustering technique, and recover modal responses combing the estimated mode shapes matrix and the learned dictionary. The experiment results on a typical cantilever beam structure illustrate that the proposed method can perform accurate dynamic parameters identification whether in underdetermined case or determined case.
Keywords: Operational modal identification, dictionary learning, inverse problem
DOI: 10.3233/JAE-209315
Journal: International Journal of Applied Electromagnetics and Mechanics, vol. 64, no. 1-4, pp. 129-136, 2020
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