Temperature Effect Separation of Structure Responses from Monitoring Data Using an Adaptive Bandwidth Filter Algorithm
Temperature is one of the most important factors significantly affecting damage detection performance in civil engineering. A new method called the Adaptive Bandwidth Filter Algorithm (ABFA) is proposed in this paper to separate the temperature effect from quasi-static long-term structural health mo...
Gespeichert in:
| Veröffentlicht in: | Materials 2024-01, Vol.17 (2), p.465 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | 2 |
| container_start_page | 465 |
| container_title | Materials |
| container_volume | 17 |
| creator | Hu, Anqing Liu, Gang Deng, Changjun Luo, Jun |
| description | Temperature is one of the most important factors significantly affecting damage detection performance in civil engineering. A new method called the Adaptive Bandwidth Filter Algorithm (ABFA) is proposed in this paper to separate the temperature effect from quasi-static long-term structural health monitoring data. The Adaptive Bandwidth Filter Algorithm (ABFA) is referred to as an algorithm of automatically adjusting the frequency bandwidth filter via the particle swarm optimization (PSO) algorithm. Considering the obvious multi-scale feature of the collected data of civil structure, the acquired time series are divided into different time scales (for example, day, month, year, etc.), and these scales in the frequency domain correspond to the center frequencies of the adaptive bandwidth filter. The temperature effect on structure responses across different time scales is thereafter explored by adaptively adjusting the frequency bandwidth of the filter based on the known center frequencies of different scales. The relationship between the temperature and the structure responses is established through statistical regression facilitated by sufficient in situ monitoring data. Simulation and experiment results show the very promising performance of the proposed algorithm and decouple the temperature effect accurately from the contaminated data; thus an enhanced capability of damage detection is achieved. |
| doi_str_mv | 10.3390/ma17020465 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11154543</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A780878713</galeid><sourcerecordid>A780878713</sourcerecordid><originalsourceid>FETCH-LOGICAL-c446t-5ac03fa3a67da653647353df0f0c1db850e1d77f686b266823e6cbf04d7eebc63</originalsourceid><addsrcrecordid>eNpdklFvFCEQxzdGY5vaFz-AIfHFmFyFhQX2yVxrqyY1JrZ9JiwMdzS7sAJ7xm_f3V6tVXhgMvOb_8yEqarXBJ9Q2uIPgyYC15jx5ll1SNqWr0jL2PMn9kF1nPMtng-lRNbty-qAyrppOK0Pq901DCMkXaYE6Nw5MAVdwahnj48BRYeuSprMffgH5DGGDBm5FAf0LQZfYvJhgz7potFNXkwd0NrqsfgdoFMd7C9vyxZd-L5AQut-MyeU7fCqeuF0n-H44T2qbi7Or8--rC6_f_56tr5cGcZ4WTXaYOo01VxYzRvKmaANtQ47bIjtZIOBWCEcl7yrOZc1BW46h5kVAJ3h9Kj6uNcdp24AayCUpHs1Jj_o9FtF7dW_keC3ahN3ihDSsIbRWeHdg0KKPyfIRQ0-G-h7HSBOWdUtEZJLQRf07X_obZxSmOdbKClEy6icqZM9tdE9KB9cnAub-VoYvIkBnJ_9ayGxFFKQRfb9PsGkmHMC99g-wWrZAfV3B2b4zdOBH9E_P07vAOCsra8</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2918779438</pqid></control><display><type>article</type><title>Temperature Effect Separation of Structure Responses from Monitoring Data Using an Adaptive Bandwidth Filter Algorithm</title><source>PubMed Central Open Access</source><source>MDPI - Multidisciplinary Digital Publishing Institute</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Hu, Anqing ; Liu, Gang ; Deng, Changjun ; Luo, Jun</creator><creatorcontrib>Hu, Anqing ; Liu, Gang ; Deng, Changjun ; Luo, Jun</creatorcontrib><description>Temperature is one of the most important factors significantly affecting damage detection performance in civil engineering. A new method called the Adaptive Bandwidth Filter Algorithm (ABFA) is proposed in this paper to separate the temperature effect from quasi-static long-term structural health monitoring data. The Adaptive Bandwidth Filter Algorithm (ABFA) is referred to as an algorithm of automatically adjusting the frequency bandwidth filter via the particle swarm optimization (PSO) algorithm. Considering the obvious multi-scale feature of the collected data of civil structure, the acquired time series are divided into different time scales (for example, day, month, year, etc.), and these scales in the frequency domain correspond to the center frequencies of the adaptive bandwidth filter. The temperature effect on structure responses across different time scales is thereafter explored by adaptively adjusting the frequency bandwidth of the filter based on the known center frequencies of different scales. The relationship between the temperature and the structure responses is established through statistical regression facilitated by sufficient in situ monitoring data. Simulation and experiment results show the very promising performance of the proposed algorithm and decouple the temperature effect accurately from the contaminated data; thus an enhanced capability of damage detection is achieved.</description><identifier>ISSN: 1996-1944</identifier><identifier>EISSN: 1996-1944</identifier><identifier>DOI: 10.3390/ma17020465</identifier><identifier>PMID: 38255632</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Adaptive algorithms ; Algorithms ; Bandwidths ; Concrete ; Damage detection ; Data collection ; Influence ; Mathematical optimization ; Methods ; Optimization ; Particle swarm optimization ; Principal components analysis ; Spectrum analysis ; Statistical analysis ; Structural health monitoring ; Temperature effects ; Time ; Wavelet transforms</subject><ispartof>Materials, 2024-01, Vol.17 (2), p.465</ispartof><rights>COPYRIGHT 2024 MDPI AG</rights><rights>2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 by the authors. 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c446t-5ac03fa3a67da653647353df0f0c1db850e1d77f686b266823e6cbf04d7eebc63</citedby><cites>FETCH-LOGICAL-c446t-5ac03fa3a67da653647353df0f0c1db850e1d77f686b266823e6cbf04d7eebc63</cites><orcidid>0000-0002-2506-0339</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11154543/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11154543/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38255632$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hu, Anqing</creatorcontrib><creatorcontrib>Liu, Gang</creatorcontrib><creatorcontrib>Deng, Changjun</creatorcontrib><creatorcontrib>Luo, Jun</creatorcontrib><title>Temperature Effect Separation of Structure Responses from Monitoring Data Using an Adaptive Bandwidth Filter Algorithm</title><title>Materials</title><addtitle>Materials (Basel)</addtitle><description>Temperature is one of the most important factors significantly affecting damage detection performance in civil engineering. A new method called the Adaptive Bandwidth Filter Algorithm (ABFA) is proposed in this paper to separate the temperature effect from quasi-static long-term structural health monitoring data. The Adaptive Bandwidth Filter Algorithm (ABFA) is referred to as an algorithm of automatically adjusting the frequency bandwidth filter via the particle swarm optimization (PSO) algorithm. Considering the obvious multi-scale feature of the collected data of civil structure, the acquired time series are divided into different time scales (for example, day, month, year, etc.), and these scales in the frequency domain correspond to the center frequencies of the adaptive bandwidth filter. The temperature effect on structure responses across different time scales is thereafter explored by adaptively adjusting the frequency bandwidth of the filter based on the known center frequencies of different scales. The relationship between the temperature and the structure responses is established through statistical regression facilitated by sufficient in situ monitoring data. Simulation and experiment results show the very promising performance of the proposed algorithm and decouple the temperature effect accurately from the contaminated data; thus an enhanced capability of damage detection is achieved.</description><subject>Adaptive algorithms</subject><subject>Algorithms</subject><subject>Bandwidths</subject><subject>Concrete</subject><subject>Damage detection</subject><subject>Data collection</subject><subject>Influence</subject><subject>Mathematical optimization</subject><subject>Methods</subject><subject>Optimization</subject><subject>Particle swarm optimization</subject><subject>Principal components analysis</subject><subject>Spectrum analysis</subject><subject>Statistical analysis</subject><subject>Structural health monitoring</subject><subject>Temperature effects</subject><subject>Time</subject><subject>Wavelet transforms</subject><issn>1996-1944</issn><issn>1996-1944</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpdklFvFCEQxzdGY5vaFz-AIfHFmFyFhQX2yVxrqyY1JrZ9JiwMdzS7sAJ7xm_f3V6tVXhgMvOb_8yEqarXBJ9Q2uIPgyYC15jx5ll1SNqWr0jL2PMn9kF1nPMtng-lRNbty-qAyrppOK0Pq901DCMkXaYE6Nw5MAVdwahnj48BRYeuSprMffgH5DGGDBm5FAf0LQZfYvJhgz7potFNXkwd0NrqsfgdoFMd7C9vyxZd-L5AQut-MyeU7fCqeuF0n-H44T2qbi7Or8--rC6_f_56tr5cGcZ4WTXaYOo01VxYzRvKmaANtQ47bIjtZIOBWCEcl7yrOZc1BW46h5kVAJ3h9Kj6uNcdp24AayCUpHs1Jj_o9FtF7dW_keC3ahN3ihDSsIbRWeHdg0KKPyfIRQ0-G-h7HSBOWdUtEZJLQRf07X_obZxSmOdbKClEy6icqZM9tdE9KB9cnAub-VoYvIkBnJ_9ayGxFFKQRfb9PsGkmHMC99g-wWrZAfV3B2b4zdOBH9E_P07vAOCsra8</recordid><startdate>20240118</startdate><enddate>20240118</enddate><creator>Hu, Anqing</creator><creator>Liu, Gang</creator><creator>Deng, Changjun</creator><creator>Luo, Jun</creator><general>MDPI AG</general><general>MDPI</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>KB.</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-2506-0339</orcidid></search><sort><creationdate>20240118</creationdate><title>Temperature Effect Separation of Structure Responses from Monitoring Data Using an Adaptive Bandwidth Filter Algorithm</title><author>Hu, Anqing ; Liu, Gang ; Deng, Changjun ; Luo, Jun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c446t-5ac03fa3a67da653647353df0f0c1db850e1d77f686b266823e6cbf04d7eebc63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Adaptive algorithms</topic><topic>Algorithms</topic><topic>Bandwidths</topic><topic>Concrete</topic><topic>Damage detection</topic><topic>Data collection</topic><topic>Influence</topic><topic>Mathematical optimization</topic><topic>Methods</topic><topic>Optimization</topic><topic>Particle swarm optimization</topic><topic>Principal components analysis</topic><topic>Spectrum analysis</topic><topic>Statistical analysis</topic><topic>Structural health monitoring</topic><topic>Temperature effects</topic><topic>Time</topic><topic>Wavelet transforms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hu, Anqing</creatorcontrib><creatorcontrib>Liu, Gang</creatorcontrib><creatorcontrib>Deng, Changjun</creatorcontrib><creatorcontrib>Luo, Jun</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Engineered Materials Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>Materials Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Materials</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hu, Anqing</au><au>Liu, Gang</au><au>Deng, Changjun</au><au>Luo, Jun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Temperature Effect Separation of Structure Responses from Monitoring Data Using an Adaptive Bandwidth Filter Algorithm</atitle><jtitle>Materials</jtitle><addtitle>Materials (Basel)</addtitle><date>2024-01-18</date><risdate>2024</risdate><volume>17</volume><issue>2</issue><spage>465</spage><pages>465-</pages><issn>1996-1944</issn><eissn>1996-1944</eissn><abstract>Temperature is one of the most important factors significantly affecting damage detection performance in civil engineering. A new method called the Adaptive Bandwidth Filter Algorithm (ABFA) is proposed in this paper to separate the temperature effect from quasi-static long-term structural health monitoring data. The Adaptive Bandwidth Filter Algorithm (ABFA) is referred to as an algorithm of automatically adjusting the frequency bandwidth filter via the particle swarm optimization (PSO) algorithm. Considering the obvious multi-scale feature of the collected data of civil structure, the acquired time series are divided into different time scales (for example, day, month, year, etc.), and these scales in the frequency domain correspond to the center frequencies of the adaptive bandwidth filter. The temperature effect on structure responses across different time scales is thereafter explored by adaptively adjusting the frequency bandwidth of the filter based on the known center frequencies of different scales. The relationship between the temperature and the structure responses is established through statistical regression facilitated by sufficient in situ monitoring data. Simulation and experiment results show the very promising performance of the proposed algorithm and decouple the temperature effect accurately from the contaminated data; thus an enhanced capability of damage detection is achieved.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>38255632</pmid><doi>10.3390/ma17020465</doi><orcidid>https://orcid.org/0000-0002-2506-0339</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1996-1944 |
| ispartof | Materials, 2024-01, Vol.17 (2), p.465 |
| issn | 1996-1944 1996-1944 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11154543 |
| source | PubMed Central Open Access; MDPI - Multidisciplinary Digital Publishing Institute; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Adaptive algorithms Algorithms Bandwidths Concrete Damage detection Data collection Influence Mathematical optimization Methods Optimization Particle swarm optimization Principal components analysis Spectrum analysis Statistical analysis Structural health monitoring Temperature effects Time Wavelet transforms |
| title | Temperature Effect Separation of Structure Responses from Monitoring Data Using an Adaptive Bandwidth Filter Algorithm |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T14%3A39%3A12IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Temperature%20Effect%20Separation%20of%20Structure%20Responses%20from%20Monitoring%20Data%20Using%20an%20Adaptive%20Bandwidth%20Filter%20Algorithm&rft.jtitle=Materials&rft.au=Hu,%20Anqing&rft.date=2024-01-18&rft.volume=17&rft.issue=2&rft.spage=465&rft.pages=465-&rft.issn=1996-1944&rft.eissn=1996-1944&rft_id=info:doi/10.3390/ma17020465&rft_dat=%3Cgale_pubme%3EA780878713%3C/gale_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2918779438&rft_id=info:pmid/38255632&rft_galeid=A780878713&rfr_iscdi=true |