A robust force identification method based on L1+2-norm approximation theory

Obtaining the real force of the structure is the basic condition for efficient vibration reduction design. However, the uneasiness and instability of the inverse problem make the force identification still challenging. On the basis of L2-norm regularization, we propose a new method for force identification based on L1+2-norm approximation theory. By introducing the L1-norm penalty operator, a joint norm approximation optimization model is constructed to limit the non-zero force and punish the force value which approaching to zero, so that it can adapt to the identification of various types of forces. Then the optimal force solution is obtained by using the Primal-dual interior point method. Finally, the effectiveness and accuracy of the proposed method are verified by numerical simulation and experiment of asymmetric plate and double-layer plate structures. Different from previous studies, the L1+2-norm method in this work has high robustness, considers the characteristics of sparse regularization and L2-norm regularization, and can adapt to the identification of continuous forces and sparse forces at the same time, which has potential engineering application value.

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Publication Details

Journal
NOISE-CON proceedings
Published
2024-10-04
DOI
https://doi.org/10.3397/in_2024_1813
Primary Topic
Hand Gesture Recognition Systems
Type
article
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article

A robust force identification method based on L1+2-norm approximation theory

Chengjun Wu, Hongli MENG, Chao Zhang
NOISE-CON proceedings
Hand Gesture Recognition Systems
article

A robust force identification method based on L1+2-norm approximation theory

Chengjun Wu, Hongli MENG, Chao Zhang
article en

Abstract

Obtaining the real force of the structure is the basic condition for efficient vibration reduction design. However, the uneasiness and instability of the inverse problem make the force identification still challenging. On the basis of L2-norm regularization, we propose a new method for force identification based on L1+2-norm approximation theory. By introducing the L1-norm penalty operator, a joint norm approximation optimization model is constructed to limit the non-zero force and punish the force value which approaching to zero, so that it can adapt to the identification of various types of forces. Then the optimal force solution is obtained by using the Primal-dual interior point method. Finally, the effectiveness and accuracy of the proposed method are verified by numerical simulation and experiment of asymmetric plate and double-layer plate structures. Different from previous studies, the L1+2-norm method in this work has high robustness, considers the characteristics of sparse regularization and L2-norm regularization, and can adapt to the identification of continuous forces and sparse forces at the same time, which has potential engineering application value.

NOISE-CON proceedingsVol. 270(11)
Xi'an Jiaotong University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 83%
Hand Gesture Recognition Systems
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A robust force identification method based on L1+2-norm approximation theory — Chengjun Wu, Hongli MENG, et al. · NOISE-CON proceedings (2024) | TGRS Research Map | TGRS