Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/106647
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Civil and Environmental Engineering | en_US |
dc.creator | Cai, Q | en_US |
dc.creator | Chen, Z | en_US |
dc.creator | Zhu, S | en_US |
dc.date.accessioned | 2024-05-27T05:16:05Z | - |
dc.date.available | 2024-05-27T05:16:05Z | - |
dc.identifier.citation | v. 28, no. 3, 04022151 | - |
dc.identifier.issn | 1084-0702 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/106647 | - |
dc.language.iso | en | en_US |
dc.publisher | American Society of Civil Engineers | en_US |
dc.rights | © 2022 American Society of Civil Engineers. | en_US |
dc.rights | This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://ascelibrary.org/doi/10.1061/JBENF2.BEENG-5893. | en_US |
dc.subject | Damage detection | en_US |
dc.subject | Influence line | en_US |
dc.subject | Long-span bridge | en_US |
dc.subject | Structural health monitoring | en_US |
dc.title | Experimental study of influence line-based damage localization for long-span cable suspension bridges | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 04022151-1 | en_US |
dc.identifier.epage | 04022151-13 | en_US |
dc.identifier.volume | 28 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.doi | 10.1061/JBENF2.BEENG-5893 | en_US |
dcterms.abstract | Influence line (IL)–based damage indices for long-span bridges are investigated in this study. Their effectiveness is experimentally validated for the first time through the scaled physical model of the Tsing Ma Bridge (TMB). First, the IL mechanism for damage detection and its corresponding damage indices are briefly introduced. Subsequently, the scaled TMB model instrumented with different types of sensors, including displacement sensors, strain gauges, and accelerometers, is introduced. The IL characteristics of different bridge components are compared. Two different damage cases with single- and double-damage locations at the bottom chord were tested. In the single-damage case, different ILs extracted from the nearby components were used for damage identification. These ILs can successfully locate damage visually. The strain IL (SIL) is more sensitive to local damage than deflection IL, but its detection performance degrades rapidly with the increasing distance between sensor and force locations. In the double-damage case, the SIL extracted from a single sensor cannot identify both damage cases because of the limited detectable range of each SIL; therefore, using multiple sensor information becomes necessary. For comparison, the modal parameters were also employed for damage detection. These experimental results validated the merits of the IL–based methods proposed for long-span bridges, indicating that IL–based damage indices are good indicators of local damage detection in long-span bridges. This finding contributes to the development of real-time techniques for damage localization in long-span bridges equipped with a structural health monitoring system. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Journal of bridge engineering, Mar. 2023, v. 28, no. 3, 04022151, p. 04022151-1 - 04022151-13 | en_US |
dcterms.isPartOf | Journal of bridge engineering | en_US |
dcterms.issued | 2023-03 | - |
dc.identifier.eissn | 1943-5592 | en_US |
dc.identifier.artn | 04022151 | en_US |
dc.description.validate | 202405 bcch | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | a2713 | - |
dc.identifier.SubFormID | 48112 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | National Key R&D Program of China; National Natural Science Foundation of China; GDSTC Key Technologies R&D Program; The Hong Kong Polytechnic University | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Journal/Magazine Article |
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File | Description | Size | Format | |
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Cai_Experimental_Study_Influence.pdf | Pre-Published version | 1.79 MB | Adobe PDF | View/Open |
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