.png){kind=icon}
返回
Structural source identification using a generalized Tikhonov regularization
.png){kind=icon}
OA
AI
DOI：10.1016/j.jsv.2014.06.027.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper addresses the problem of identifying mechanical exciting forces from vibration measurements. The proposed approach is based on a generalized Tikhonov regularization that allows taking into account prior information on the measurement noise as well as on the main characteristics of sources to identify like its sparsity or regularity. To solve such a regularization problem efficiently, a Generalized Iteratively Reweighted Least-Squares (GIRLS) algorithm is introduced. Proposed numerical and experimental validations reveal the crucial role of prior information in the quality of the source identification and the performance of the GIRLS algorithm. (C) 2014 Elsevier Ltd. All rights reserved.
Keyword:
REWEIGHTED LEAST-SQUARES
BORNE TRANSMISSION PATHS
FORCE IDENTIFICATION
INVERSE METHODS
VARIATIONAL APPROACH
MINIMIZATION
QUANTIFICATION
RECONSTRUCTION
LOCALIZATION
VALIDATION
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.9
论文数:
1.7W
被引数:
4.8W
机构
暂无机构信息
引用论文
.png){kind=icon}
分享收藏
查看更多内容