正规化(语言学)
Tikhonov正则化
反问题
鉴定(生物学)
计算
计算机科学
结构健康监测
克里金
甲板
系统标识
算法
数学优化
结构工程
工程类
数据挖掘
人工智能
数学
机器学习
数学分析
生物
植物
度量(数据仓库)
作者
Maria Rashidi,Shabnam Tashakori,Hamed Kalhori,Mohammad Bahmanpour,Bing Li
出处
期刊:Sensors
[MDPI AG]
日期:2023-11-18
卷期号:23 (22): 9257-9257
被引量:7
摘要
Steel-reinforced concrete decks are prominently utilized in various civil structures such as bridges and railways, where they are susceptible to unforeseen impact forces during their operational lifespan. The precise identification of the impact events holds a pivotal role in the robust health monitoring of these structures. However, direct measurement is not usually possible due to structural limitations that restrict arbitrary sensor placement. To address this challenge, inverse identification emerges as a plausible solution, albeit afflicted by the issue of ill-posedness. In tackling such ill-conditioned challenges, the iterative regularization technique known as the Landweber method proves valuable. This technique leads to a more reliable and accurate solution compared with traditional direct regularization methods and it is, additionally, more suitable for large-scale problems due to the alleviated computation burden. This paper employs the Landweber method to perform a comprehensive impact force identification encompassing impact localization and impact time–history reconstruction. The incorporation of a low-pass filter within the Landweber-based identification procedure is proposed to augment the reconstruction process. Moreover, a standardized reconstruction error metric is presented, offering a more effective means of accuracy assessment. A detailed discussion on sensor placement and the optimal number of regularization iterations is presented. To automatedly localize the impact force, a Gaussian profile is proposed, against which reconstructed impact forces are compared. The efficacy of the proposed techniques is illustrated by utilizing the experimental data acquired from a bridge concrete deck reinforced with a steel beam.
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