Damage detection of highway bridges based on long-gauge strain response under stochastic traffic flow
•Good performance in identifying damage location and extent for highway bridges.•Traffic flow conditions have little effect on damage identification results.•Applicable for rapid diagnosis and long-term monitoring of bridges.•The sensor layout is same as other techniques like weigh-in-motion in SHM....
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Veröffentlicht in: | Mechanical systems and signal processing 2019-07, Vol.127, p.551-572 |
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description | •Good performance in identifying damage location and extent for highway bridges.•Traffic flow conditions have little effect on damage identification results.•Applicable for rapid diagnosis and long-term monitoring of bridges.•The sensor layout is same as other techniques like weigh-in-motion in SHM.•The efficiency and cost for highway bridge SHM can be greatly improved.
Highway bridges are essential infrastructure engineering. To monitor their conditions effectively, bridge structural health monitoring (SHM) techniques have been developed to substitute the manual inspection. Among SHM techniques, the damage detection method is the most promising one utilized for identifying damage location and extent. However, most frequency-domain signal based damage detection methods are not sufficiently sensitive to local damage, while other time-domain signal based methods with a sufficient sensitivity have many limitations, especially on working conditions where those methods are only feasible when just a single vehicle passes over the bridge. This restriction severely differs with actual traffic situations. Under these backgrounds, in this study, a damage detection method based on long-gauge fibre Bragg grating (FBG) was proposed, which can achieve the identification of the damage location and extent under stochastic traffic flow. This method’s feasibility was initially verified through a series of indoor bridge model experiments. Then, some numerical case studies were conducted to mimic actual stochastic traffic flow conditions. The results of experiment and numerical simulation demonstrated that this method performs well in detecting the damage location and extent under various designed situations, and it has the potential to be an alternative for the current methods. |
doi_str_mv | 10.1016/j.ymssp.2019.03.022 |
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Highway bridges are essential infrastructure engineering. To monitor their conditions effectively, bridge structural health monitoring (SHM) techniques have been developed to substitute the manual inspection. Among SHM techniques, the damage detection method is the most promising one utilized for identifying damage location and extent. However, most frequency-domain signal based damage detection methods are not sufficiently sensitive to local damage, while other time-domain signal based methods with a sufficient sensitivity have many limitations, especially on working conditions where those methods are only feasible when just a single vehicle passes over the bridge. This restriction severely differs with actual traffic situations. Under these backgrounds, in this study, a damage detection method based on long-gauge fibre Bragg grating (FBG) was proposed, which can achieve the identification of the damage location and extent under stochastic traffic flow. This method’s feasibility was initially verified through a series of indoor bridge model experiments. Then, some numerical case studies were conducted to mimic actual stochastic traffic flow conditions. The results of experiment and numerical simulation demonstrated that this method performs well in detecting the damage location and extent under various designed situations, and it has the potential to be an alternative for the current methods.</description><identifier>ISSN: 0888-3270</identifier><identifier>EISSN: 1096-1216</identifier><identifier>DOI: 10.1016/j.ymssp.2019.03.022</identifier><language>eng</language><publisher>Berlin: Elsevier Ltd</publisher><subject>Computer simulation ; Damage detection ; Feasibility ; Highway bridges ; Inspection ; Long-gauge fibre Bragg grating ; Mathematical models ; Methods ; Stochastic traffic flow ; Strain gauges ; Structural health monitoring ; Time domain analysis ; Traffic flow</subject><ispartof>Mechanical systems and signal processing, 2019-07, Vol.127, p.551-572</ispartof><rights>2019 Elsevier Ltd</rights><rights>Copyright Elsevier BV Jul 15, 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c331t-fefeae5f7b3338f7aa8cac401998700b2cc5f329cfbdc958bb58e860c9180bb03</citedby><cites>FETCH-LOGICAL-c331t-fefeae5f7b3338f7aa8cac401998700b2cc5f329cfbdc958bb58e860c9180bb03</cites><orcidid>0000-0002-9405-3757</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ymssp.2019.03.022$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Chen, Shi-Zhi</creatorcontrib><creatorcontrib>Wu, Gang</creatorcontrib><creatorcontrib>Feng, De-Cheng</creatorcontrib><title>Damage detection of highway bridges based on long-gauge strain response under stochastic traffic flow</title><title>Mechanical systems and signal processing</title><description>•Good performance in identifying damage location and extent for highway bridges.•Traffic flow conditions have little effect on damage identification results.•Applicable for rapid diagnosis and long-term monitoring of bridges.•The sensor layout is same as other techniques like weigh-in-motion in SHM.•The efficiency and cost for highway bridge SHM can be greatly improved.
Highway bridges are essential infrastructure engineering. To monitor their conditions effectively, bridge structural health monitoring (SHM) techniques have been developed to substitute the manual inspection. Among SHM techniques, the damage detection method is the most promising one utilized for identifying damage location and extent. However, most frequency-domain signal based damage detection methods are not sufficiently sensitive to local damage, while other time-domain signal based methods with a sufficient sensitivity have many limitations, especially on working conditions where those methods are only feasible when just a single vehicle passes over the bridge. This restriction severely differs with actual traffic situations. Under these backgrounds, in this study, a damage detection method based on long-gauge fibre Bragg grating (FBG) was proposed, which can achieve the identification of the damage location and extent under stochastic traffic flow. This method’s feasibility was initially verified through a series of indoor bridge model experiments. Then, some numerical case studies were conducted to mimic actual stochastic traffic flow conditions. The results of experiment and numerical simulation demonstrated that this method performs well in detecting the damage location and extent under various designed situations, and it has the potential to be an alternative for the current methods.</description><subject>Computer simulation</subject><subject>Damage detection</subject><subject>Feasibility</subject><subject>Highway bridges</subject><subject>Inspection</subject><subject>Long-gauge fibre Bragg grating</subject><subject>Mathematical models</subject><subject>Methods</subject><subject>Stochastic traffic flow</subject><subject>Strain gauges</subject><subject>Structural health monitoring</subject><subject>Time domain analysis</subject><subject>Traffic flow</subject><issn>0888-3270</issn><issn>1096-1216</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp9kM1OwzAQhC0EEqXwBFwscU5Y223iHDig8itV4gJny3bWqaM2LnYK6tvjUs6cRtrZ2dV8hFwzKBmw6rYv95uUtiUH1pQgSuD8hEwYNFXBOKtOyQSklIXgNZyTi5R6AGhmUE0IPuiN7pC2OKIdfRhocHTlu9W33lMTfdthokYnbGn21mHoik7vciCNUfuBRkzbMCSku6HFmKfBrnQavaXZdy6rW4fvS3Lm9Drh1Z9OycfT4_vipVi-Pb8u7peFFYKNhUOHGueuNkII6WqtpdV2lks1sgYw3Nq5E7yxzrS2mUtj5hJlBbZhEowBMSU3x7vbGD53mEbVh10c8kvFeb4jJIfDljhu2RhSiujUNvqNjnvFQB14ql798lQHngqEyjxz6u6Ywlzgy2NUyXocLLY-ZnSqDf7f_A-BwYG-</recordid><startdate>20190715</startdate><enddate>20190715</enddate><creator>Chen, Shi-Zhi</creator><creator>Wu, Gang</creator><creator>Feng, De-Cheng</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-9405-3757</orcidid></search><sort><creationdate>20190715</creationdate><title>Damage detection of highway bridges based on long-gauge strain response under stochastic traffic flow</title><author>Chen, Shi-Zhi ; Wu, Gang ; Feng, De-Cheng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c331t-fefeae5f7b3338f7aa8cac401998700b2cc5f329cfbdc958bb58e860c9180bb03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Computer simulation</topic><topic>Damage detection</topic><topic>Feasibility</topic><topic>Highway bridges</topic><topic>Inspection</topic><topic>Long-gauge fibre Bragg grating</topic><topic>Mathematical models</topic><topic>Methods</topic><topic>Stochastic traffic flow</topic><topic>Strain gauges</topic><topic>Structural health monitoring</topic><topic>Time domain analysis</topic><topic>Traffic flow</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Shi-Zhi</creatorcontrib><creatorcontrib>Wu, Gang</creatorcontrib><creatorcontrib>Feng, De-Cheng</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Mechanical systems and signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Shi-Zhi</au><au>Wu, Gang</au><au>Feng, De-Cheng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Damage detection of highway bridges based on long-gauge strain response under stochastic traffic flow</atitle><jtitle>Mechanical systems and signal processing</jtitle><date>2019-07-15</date><risdate>2019</risdate><volume>127</volume><spage>551</spage><epage>572</epage><pages>551-572</pages><issn>0888-3270</issn><eissn>1096-1216</eissn><abstract>•Good performance in identifying damage location and extent for highway bridges.•Traffic flow conditions have little effect on damage identification results.•Applicable for rapid diagnosis and long-term monitoring of bridges.•The sensor layout is same as other techniques like weigh-in-motion in SHM.•The efficiency and cost for highway bridge SHM can be greatly improved.
Highway bridges are essential infrastructure engineering. To monitor their conditions effectively, bridge structural health monitoring (SHM) techniques have been developed to substitute the manual inspection. Among SHM techniques, the damage detection method is the most promising one utilized for identifying damage location and extent. However, most frequency-domain signal based damage detection methods are not sufficiently sensitive to local damage, while other time-domain signal based methods with a sufficient sensitivity have many limitations, especially on working conditions where those methods are only feasible when just a single vehicle passes over the bridge. This restriction severely differs with actual traffic situations. Under these backgrounds, in this study, a damage detection method based on long-gauge fibre Bragg grating (FBG) was proposed, which can achieve the identification of the damage location and extent under stochastic traffic flow. This method’s feasibility was initially verified through a series of indoor bridge model experiments. Then, some numerical case studies were conducted to mimic actual stochastic traffic flow conditions. The results of experiment and numerical simulation demonstrated that this method performs well in detecting the damage location and extent under various designed situations, and it has the potential to be an alternative for the current methods.</abstract><cop>Berlin</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.ymssp.2019.03.022</doi><tpages>22</tpages><orcidid>https://orcid.org/0000-0002-9405-3757</orcidid></addata></record> |
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subjects | Computer simulation Damage detection Feasibility Highway bridges Inspection Long-gauge fibre Bragg grating Mathematical models Methods Stochastic traffic flow Strain gauges Structural health monitoring Time domain analysis Traffic flow |
title | Damage detection of highway bridges based on long-gauge strain response under stochastic traffic flow |
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