Residential College | false |
Status | 已發表Published |
Monitoring gross vehicle weight with a probabilistic and influence line-free bridge weight-in-motion scheme based on a transmissibility-like index | |
Yan, Wang Ji1,2; Hao, Teng Teng1; Yuen, Ka Veng1,2; Papadimitriou, Costas3 | |
2022-09-01 | |
Source Publication | MECHANICAL SYSTEMS AND SIGNAL PROCESSING |
ISSN | 0888-3270 |
Volume | 177Pages:109133 |
Abstract | A new transmissibility-like index defined as the ratio of the frequency responses of the same monitoring location under two different loading conditions was proposed for Gross Vehicle Weights (GVWs) monitoring in this study. Based on the theoretical finding that the displacements of a beam subjected to moving loads were the convolution of the load and the influence line, the equivalence between the transmissibility-like index at the zero frequency and the ratio of two GVWs under two-moving-load scenarios was theoretically revealed. Given the reference responses for known moving loads, an influence line-free algorithm was proposed to estimate the GVW of an arbitrary vehicle by making full use of the unique property of the new transmissibility-like index. To accommodate various uncertainties and fuse the measurements of different channels simultaneously, the problem of Bridge Weigh-In-Motion (B-WIM) was formulated in the framework of Bayesian inference with the aid of a complex Gaussian ratio probabilistic model of transmissibility function. The posterior distribution of the GVW was derived analytically. By applying the proposed transmissibility-like index, this method possessed an obvious advantage in achieving robust GVWs without the requirement of any knowledge of the bridge model such as the influence line. Two applications, including a numerical example and an experimental verification, were used to demonstrate the efficiency and accuracy of the statistical and influence line-free B-WIM scheme. |
Keyword | Bayesian Analysis Bridge Weight-in-motion Influence Line Moving Loads Transmissibility |
DOI | 10.1016/j.ymssp.2022.109133 |
URL | View the original |
Indexed By | SCIE |
Language | 英語English |
WOS Research Area | Engineering |
WOS Subject | Engineering, Mechanical |
WOS ID | WOS:000799273400003 |
Scopus ID | 2-s2.0-85129070956 |
Fulltext Access | |
Citation statistics | |
Document Type | Journal article |
Collection | DEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING Faculty of Science and Technology THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU) |
Corresponding Author | Yan, Wang Ji |
Affiliation | 1.State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering, University of Macau, Macau, China 2.Guangdong–Hong Kong-Macau Joint Laboratory for Smart Cities, University of Macau, China 3.Department of Mechanical Engineering, University of Thessaly, Greece |
First Author Affilication | University of Macau |
Corresponding Author Affilication | University of Macau |
Recommended Citation GB/T 7714 | Yan, Wang Ji,Hao, Teng Teng,Yuen, Ka Veng,et al. Monitoring gross vehicle weight with a probabilistic and influence line-free bridge weight-in-motion scheme based on a transmissibility-like index[J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2022, 177, 109133. |
APA | Yan, Wang Ji., Hao, Teng Teng., Yuen, Ka Veng., & Papadimitriou, Costas (2022). Monitoring gross vehicle weight with a probabilistic and influence line-free bridge weight-in-motion scheme based on a transmissibility-like index. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 177, 109133. |
MLA | Yan, Wang Ji,et al."Monitoring gross vehicle weight with a probabilistic and influence line-free bridge weight-in-motion scheme based on a transmissibility-like index".MECHANICAL SYSTEMS AND SIGNAL PROCESSING 177(2022):109133. |
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