| Title: | Using statistical analysis of an acceleration-based bridge weigh-in-motion system for damage detection |
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| Authors: | ID O'Brien, Eugene J. (Author)
ID Khan, Muhammad Arslan (Author)
ID McCrum, Daniel Patrick (Author)
ID Žnidarič, Aleš (Author) |
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| Files: |  URL - Source URL, visit https://www.mdpi.com/2076-3417/10/2/663
Description: Open Access
 PDF - Presentation file, download (8,01 MB)
MD5: 9BB19601ABEA1618EE745D7B3A377734
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| Language: | English |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: |  ZAG - Slovenian National Building and Civil Engineering Institute
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| Abstract: | This paper develops a novel method of bridge damage detection using statistical analysis of data from an acceleration-based bridge weigh-in-motion (BWIM) system. Bridge dynamic analysis using a vehicle-bridge interaction model is carried out to obtain bridge accelerations, and the BWIM concept is applied to infer the vehicle axle weights. A large volume of traffic data tends to remain consistent (e.g., most frequent gross vehicle weight (GVW) of 3-axle trucks); therefore, the statistical properties of inferred vehicle weights are used to develop a bridge damage detection technique. Global change of bridge stiffness due to a change in the elastic modulus of concrete is used as a proxy of bridge damage. This approach has the advantage of overcoming the variability in acceleration signals due to the wide variety of source excitations/vehicles–data from a large number of different vehicles can be easily combined in the form of inferred vehicle weight. One year of experimental data from a short-span reinforced concrete bridge in Slovenia is used to assess the effectiveness of the new approach. Although the acceleration-based BWIM system is inaccurate for finding vehicle axle-weights, it is found to be effective in detecting damage using statistical analysis. It is shown through simulation as well as by experimental analysis that a significant change in the statistical properties of the inferred BWIM data results from changes in the bridge condition. |
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| Keywords: | bridge health monitoring, bridge WIM, structural dynamics, damage detection, vehicle-bridge interaction |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Publication date: | 17.01.2020 |
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| Publisher: | MDPI |
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| Year of publishing: | 2020 |
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| Number of pages: | str. 1-20 |
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| Numbering: | Vol. 10, iss. 2 |
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| PID: | 20.500.12556/DiRROS-16940  |
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| UDC: | 624 |
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| ISSN on article: | 2076-3417 |
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| DOI: | 10.3390/app10020663 |
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| COBISS.SI-ID: | 2515047 |
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| Copyright: |
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Open AccessArticle
Using Statistical Analysis of an Acceleration-Based Bridge Weigh-In-Motion System for Damage Detection
by Eugene OBrien
1 [ORCID] , Muhammad Arslan Khan
1,* [ORCID] , Daniel Patrick McCrum
1 [ORCID] and Aleš Žnidarič
2
1
School of Civil Engineering, University College Dublin, D04 V1W8 Belfield, Ireland
2
Slovenian National Building and Civil Engineering Institute (ZAG), 1000 Ljubljana, Slovenia
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(2), 663; https://doi.org/10.3390/app10020663
Received: 9 December 2019 / Revised: 13 January 2020 / Accepted: 14 January 2020 / Published: 17 January 2020
(This article belongs to the Section Civil Engineering)
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Abstract
This paper develops a novel method of bridge damage detection using statistical analysis of data from an acceleration-based bridge weigh-in-motion (BWIM) system. Bridge dynamic analy |
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| Note: | Nasl. z nasl. zaslona;
Opis vira z dne 21. 1. 2020;
Art. 663;
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| Publication date in DiRROS: | 12.09.2023 |
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| Views: | 776 |
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| Downloads: | 333 |
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