A Novel Inverse Time–Frequency Domain Approach to Identify Random Forces

You Jia, Ruikai Li, Yanhong Fan and Haijie Huang
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You Jia: Department of Mechanics, College of Applied Science, Taiyuan University of Science and Technology, Taiyuan 030024, China
Ruikai Li: Department of Mechanics, College of Applied Science, Taiyuan University of Science and Technology, Taiyuan 030024, China
Yanhong Fan: Department of Mechanics, College of Applied Science, Taiyuan University of Science and Technology, Taiyuan 030024, China
Haijie Huang: Department of Mechanics, College of Applied Science, Taiyuan University of Science and Technology, Taiyuan 030024, China

Mathematics, 2022, vol. 10, issue 13, 1-10

Abstract: In order to ensure the reliability and safety of complex engineering structures and allow their redesign and evaluation, the estimation of dynamic loads applied on them is vital. In this paper, a novel time–frequency domain approach is proposed to identify random forces based on the weighted regularization algorithm. Firstly, the Newmark’s algorithm was applied to obtain structural dynamic responses, then a weighed regularization algorithm was used to identify the random forces exerted on the engineering structure. The weighting matrix was used to control the identified error of the random forces. A spatial frame model was built to illustrate the practicality of the proposed approach. The experimental results demonstrated that the proposed method is more effective than other methods for random forces identification.

Keywords: load identification; random force; weighting matrix; regularization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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