2020
DOI: 10.1016/j.ymssp.2019.106493
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Dynamic force identification based on composite trigonometric wavelet shape function

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Cited by 37 publications
(7 citation statements)
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“…X(t) and F(t) can be converted into Equations ( 10) and ( 11) by means of Equations ( 6) and (7). X(t) = S(t)α ( 10)…”
Section: Parametric Expression Of Structural Responses and External Loadsmentioning
confidence: 99%
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“…X(t) and F(t) can be converted into Equations ( 10) and ( 11) by means of Equations ( 6) and (7). X(t) = S(t)α ( 10)…”
Section: Parametric Expression Of Structural Responses and External Loadsmentioning
confidence: 99%
“…For this reason, much research has been carried out on the modeling of random loads. He et al represented the loads to be identified by means of the second-generation Lagrangian wavelet [ 6 , 7 ]. Lei et al applied the Daubechies wavelet to fit spatially distributed dynamic loads [ 8 ].…”
Section: Introductionmentioning
confidence: 99%
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“…With the rapid development of the national economy, increasing traffic volume, vehicle high-speed driving, and overloading during service can adversely affect the safety of bridges, posing a significant threat to their integrity and stability [1][2][3]. In the field of bridge engineering, identifying and monitoring moving loads effectively and studying the impact of bridge vibration and damage on operational performance have become urgent and important problems that need to be solved [4][5][6]. Since the problem of self-loading identification was first introduced, scholars have conducted extensive research and achieved numerous results.…”
Section: Introductionmentioning
confidence: 99%
“…It still retains its researchable charm in the field of force identification (Jayalakshmi et al, 2018; Li and Lu, 2018; Wang et al, 2018a). Many regularization techniques have been introduced for solving the problem of force identification, for example, Tikhonov method (He et al, 2019; Wang et al, 2018b), truncated singular value decomposition (Chen et al, 2019), multiplicative regularization (Aucejo and De Smet, 2018), sparse regularization (Qiao et al, 2019), and so on. Among these methods, the sparse regularization method is a comparatively new technology.…”
Section: Introductionmentioning
confidence: 99%