Semi-automated impact device based on human behaviour recognition model for in-service modal analysis
Modal analysis is a reliable method for the study of structural behaviour. A novel modal analysis technique called impact synchronous modal analysis (ISMA) was developed using which modal analysis can be performed in the presence of ambient forces. However, studies determined that the manual operati...
Gespeichert in:
Veröffentlicht in: | Journal of the Brazilian Society of Mechanical Sciences and Engineering 2023-02, Vol.45 (2), Article 96 |
---|---|
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 | |
container_title | Journal of the Brazilian Society of Mechanical Sciences and Engineering |
container_volume | 45 |
creator | Zahid, Fahad Bin Ong, Zhi Chao Khoo, Shin Yee Mohd Salleh, Mohd Fairuz |
description | Modal analysis is a reliable method for the study of structural behaviour. A novel modal analysis technique called impact synchronous modal analysis (ISMA) was developed using which modal analysis can be performed in the presence of ambient forces. However, studies determined that the manual operation of this technique is laborious, time intensive and has limited practicality due to the lack of control and knowledge of the impact with respect to the phase angle of the disturbances using conventional impact hammer. A fully automated impact device called automated phase controlled impact device (APCID) was developed to perform in-service modal analysis with minimum number of impacts. However, large size and heavy weight of this device made it unsuitable for real world applications. In this paper, a portable semi-automated impact device is used to perform in-service modal analysis. The device uses the conventional manual impact hammer and is equipped with inertial measurement unit (IMU). It is operated manually and uses human behaviour recognition along with control of APCID which gives indication to impart impact based on human’s physical behaviour. This physical behaviour is recognized by classifying different impact types and predicting impact times using machine learning technique from the inertial sensor data. The cyclic load components at 20 Hz and 30 Hz are reduced by 91.2% and 92.5%, respectively, using the proposed ISMA with IMU. The extracted modal parameters are also in good correlation with the benchmark, experimental modal analysis data as well as the previous work using APCID. All the modes are identified with less than 3% difference in natural frequencies, less than 10% difference in damping values and modal assurance criterion values greater than 0.9 for all modes at running frequencies of 20 Hz and 30 Hz. |
doi_str_mv | 10.1007/s40430-023-04022-2 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2766756466</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2766756466</sourcerecordid><originalsourceid>FETCH-LOGICAL-c319t-4020e6808596d89390e2b835833bece97deb5663d54722cbfa3961258a2a76a53</originalsourceid><addsrcrecordid>eNp9kEtLxDAUhYMoOI7-AVcB19E8mkeXMvgCwYW6Dml7O5OhbcakHZh_b5wK7lzdy73nOxwOQteM3jJK9V0qaCEooVwQWlDOCT9BC2aoIkKV7DTvShsijTbn6CKlLaWCSyUXCN6h98RNY-jdCA32_c7VI25g72vAlUv5Fga8mXo34Ao2bu_DFHGEOqwHP_r860MDHW5DxH4gCeKRzEfXYTe47pB8ukRnresSXP3OJfp8fPhYPZPXt6eX1f0rqQUrR5KTU1CGGlmqxpSipMArI6QRooIaSt1AJZUSjSw053XVOlEqxqVx3GnlpFiim9l3F8PXBGm025w2h0iWa6W0VEXGl4jPqjqGlCK0dhd97-LBMmp_6rRznTbXaY91Wp4hMUMpi4c1xD_rf6hvJ5B4GA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2766756466</pqid></control><display><type>article</type><title>Semi-automated impact device based on human behaviour recognition model for in-service modal analysis</title><source>SpringerLink Journals - AutoHoldings</source><creator>Zahid, Fahad Bin ; Ong, Zhi Chao ; Khoo, Shin Yee ; Mohd Salleh, Mohd Fairuz</creator><creatorcontrib>Zahid, Fahad Bin ; Ong, Zhi Chao ; Khoo, Shin Yee ; Mohd Salleh, Mohd Fairuz</creatorcontrib><description>Modal analysis is a reliable method for the study of structural behaviour. A novel modal analysis technique called impact synchronous modal analysis (ISMA) was developed using which modal analysis can be performed in the presence of ambient forces. However, studies determined that the manual operation of this technique is laborious, time intensive and has limited practicality due to the lack of control and knowledge of the impact with respect to the phase angle of the disturbances using conventional impact hammer. A fully automated impact device called automated phase controlled impact device (APCID) was developed to perform in-service modal analysis with minimum number of impacts. However, large size and heavy weight of this device made it unsuitable for real world applications. In this paper, a portable semi-automated impact device is used to perform in-service modal analysis. The device uses the conventional manual impact hammer and is equipped with inertial measurement unit (IMU). It is operated manually and uses human behaviour recognition along with control of APCID which gives indication to impart impact based on human’s physical behaviour. This physical behaviour is recognized by classifying different impact types and predicting impact times using machine learning technique from the inertial sensor data. The cyclic load components at 20 Hz and 30 Hz are reduced by 91.2% and 92.5%, respectively, using the proposed ISMA with IMU. The extracted modal parameters are also in good correlation with the benchmark, experimental modal analysis data as well as the previous work using APCID. All the modes are identified with less than 3% difference in natural frequencies, less than 10% difference in damping values and modal assurance criterion values greater than 0.9 for all modes at running frequencies of 20 Hz and 30 Hz.</description><identifier>ISSN: 1678-5878</identifier><identifier>EISSN: 1806-3691</identifier><identifier>DOI: 10.1007/s40430-023-04022-2</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Automation ; Cyclic loads ; Damping ; Engineering ; Hammers ; Human behavior ; Impact analysis ; Impact prediction ; Inertial platforms ; Inertial sensing devices ; Machine learning ; Mechanical Engineering ; Modal analysis ; Modal assurance criterion ; Portable equipment ; Recognition ; Resonant frequencies ; Technical Paper</subject><ispartof>Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2023-02, Vol.45 (2), Article 96</ispartof><rights>The Author(s), under exclusive licence to The Brazilian Society of Mechanical Sciences and Engineering 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-4020e6808596d89390e2b835833bece97deb5663d54722cbfa3961258a2a76a53</citedby><cites>FETCH-LOGICAL-c319t-4020e6808596d89390e2b835833bece97deb5663d54722cbfa3961258a2a76a53</cites><orcidid>0000-0002-1686-3551</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s40430-023-04022-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s40430-023-04022-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27922,27923,41486,42555,51317</link.rule.ids></links><search><creatorcontrib>Zahid, Fahad Bin</creatorcontrib><creatorcontrib>Ong, Zhi Chao</creatorcontrib><creatorcontrib>Khoo, Shin Yee</creatorcontrib><creatorcontrib>Mohd Salleh, Mohd Fairuz</creatorcontrib><title>Semi-automated impact device based on human behaviour recognition model for in-service modal analysis</title><title>Journal of the Brazilian Society of Mechanical Sciences and Engineering</title><addtitle>J Braz. Soc. Mech. Sci. Eng</addtitle><description>Modal analysis is a reliable method for the study of structural behaviour. A novel modal analysis technique called impact synchronous modal analysis (ISMA) was developed using which modal analysis can be performed in the presence of ambient forces. However, studies determined that the manual operation of this technique is laborious, time intensive and has limited practicality due to the lack of control and knowledge of the impact with respect to the phase angle of the disturbances using conventional impact hammer. A fully automated impact device called automated phase controlled impact device (APCID) was developed to perform in-service modal analysis with minimum number of impacts. However, large size and heavy weight of this device made it unsuitable for real world applications. In this paper, a portable semi-automated impact device is used to perform in-service modal analysis. The device uses the conventional manual impact hammer and is equipped with inertial measurement unit (IMU). It is operated manually and uses human behaviour recognition along with control of APCID which gives indication to impart impact based on human’s physical behaviour. This physical behaviour is recognized by classifying different impact types and predicting impact times using machine learning technique from the inertial sensor data. The cyclic load components at 20 Hz and 30 Hz are reduced by 91.2% and 92.5%, respectively, using the proposed ISMA with IMU. The extracted modal parameters are also in good correlation with the benchmark, experimental modal analysis data as well as the previous work using APCID. All the modes are identified with less than 3% difference in natural frequencies, less than 10% difference in damping values and modal assurance criterion values greater than 0.9 for all modes at running frequencies of 20 Hz and 30 Hz.</description><subject>Automation</subject><subject>Cyclic loads</subject><subject>Damping</subject><subject>Engineering</subject><subject>Hammers</subject><subject>Human behavior</subject><subject>Impact analysis</subject><subject>Impact prediction</subject><subject>Inertial platforms</subject><subject>Inertial sensing devices</subject><subject>Machine learning</subject><subject>Mechanical Engineering</subject><subject>Modal analysis</subject><subject>Modal assurance criterion</subject><subject>Portable equipment</subject><subject>Recognition</subject><subject>Resonant frequencies</subject><subject>Technical Paper</subject><issn>1678-5878</issn><issn>1806-3691</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kEtLxDAUhYMoOI7-AVcB19E8mkeXMvgCwYW6Dml7O5OhbcakHZh_b5wK7lzdy73nOxwOQteM3jJK9V0qaCEooVwQWlDOCT9BC2aoIkKV7DTvShsijTbn6CKlLaWCSyUXCN6h98RNY-jdCA32_c7VI25g72vAlUv5Fga8mXo34Ao2bu_DFHGEOqwHP_r860MDHW5DxH4gCeKRzEfXYTe47pB8ukRnresSXP3OJfp8fPhYPZPXt6eX1f0rqQUrR5KTU1CGGlmqxpSipMArI6QRooIaSt1AJZUSjSw053XVOlEqxqVx3GnlpFiim9l3F8PXBGm025w2h0iWa6W0VEXGl4jPqjqGlCK0dhd97-LBMmp_6rRznTbXaY91Wp4hMUMpi4c1xD_rf6hvJ5B4GA</recordid><startdate>20230201</startdate><enddate>20230201</enddate><creator>Zahid, Fahad Bin</creator><creator>Ong, Zhi Chao</creator><creator>Khoo, Shin Yee</creator><creator>Mohd Salleh, Mohd Fairuz</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-1686-3551</orcidid></search><sort><creationdate>20230201</creationdate><title>Semi-automated impact device based on human behaviour recognition model for in-service modal analysis</title><author>Zahid, Fahad Bin ; Ong, Zhi Chao ; Khoo, Shin Yee ; Mohd Salleh, Mohd Fairuz</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-4020e6808596d89390e2b835833bece97deb5663d54722cbfa3961258a2a76a53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Automation</topic><topic>Cyclic loads</topic><topic>Damping</topic><topic>Engineering</topic><topic>Hammers</topic><topic>Human behavior</topic><topic>Impact analysis</topic><topic>Impact prediction</topic><topic>Inertial platforms</topic><topic>Inertial sensing devices</topic><topic>Machine learning</topic><topic>Mechanical Engineering</topic><topic>Modal analysis</topic><topic>Modal assurance criterion</topic><topic>Portable equipment</topic><topic>Recognition</topic><topic>Resonant frequencies</topic><topic>Technical Paper</topic><toplevel>online_resources</toplevel><creatorcontrib>Zahid, Fahad Bin</creatorcontrib><creatorcontrib>Ong, Zhi Chao</creatorcontrib><creatorcontrib>Khoo, Shin Yee</creatorcontrib><creatorcontrib>Mohd Salleh, Mohd Fairuz</creatorcontrib><collection>CrossRef</collection><jtitle>Journal of the Brazilian Society of Mechanical Sciences and Engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zahid, Fahad Bin</au><au>Ong, Zhi Chao</au><au>Khoo, Shin Yee</au><au>Mohd Salleh, Mohd Fairuz</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Semi-automated impact device based on human behaviour recognition model for in-service modal analysis</atitle><jtitle>Journal of the Brazilian Society of Mechanical Sciences and Engineering</jtitle><stitle>J Braz. Soc. Mech. Sci. Eng</stitle><date>2023-02-01</date><risdate>2023</risdate><volume>45</volume><issue>2</issue><artnum>96</artnum><issn>1678-5878</issn><eissn>1806-3691</eissn><abstract>Modal analysis is a reliable method for the study of structural behaviour. A novel modal analysis technique called impact synchronous modal analysis (ISMA) was developed using which modal analysis can be performed in the presence of ambient forces. However, studies determined that the manual operation of this technique is laborious, time intensive and has limited practicality due to the lack of control and knowledge of the impact with respect to the phase angle of the disturbances using conventional impact hammer. A fully automated impact device called automated phase controlled impact device (APCID) was developed to perform in-service modal analysis with minimum number of impacts. However, large size and heavy weight of this device made it unsuitable for real world applications. In this paper, a portable semi-automated impact device is used to perform in-service modal analysis. The device uses the conventional manual impact hammer and is equipped with inertial measurement unit (IMU). It is operated manually and uses human behaviour recognition along with control of APCID which gives indication to impart impact based on human’s physical behaviour. This physical behaviour is recognized by classifying different impact types and predicting impact times using machine learning technique from the inertial sensor data. The cyclic load components at 20 Hz and 30 Hz are reduced by 91.2% and 92.5%, respectively, using the proposed ISMA with IMU. The extracted modal parameters are also in good correlation with the benchmark, experimental modal analysis data as well as the previous work using APCID. All the modes are identified with less than 3% difference in natural frequencies, less than 10% difference in damping values and modal assurance criterion values greater than 0.9 for all modes at running frequencies of 20 Hz and 30 Hz.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s40430-023-04022-2</doi><orcidid>https://orcid.org/0000-0002-1686-3551</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1678-5878 |
ispartof | Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2023-02, Vol.45 (2), Article 96 |
issn | 1678-5878 1806-3691 |
language | eng |
recordid | cdi_proquest_journals_2766756466 |
source | SpringerLink Journals - AutoHoldings |
subjects | Automation Cyclic loads Damping Engineering Hammers Human behavior Impact analysis Impact prediction Inertial platforms Inertial sensing devices Machine learning Mechanical Engineering Modal analysis Modal assurance criterion Portable equipment Recognition Resonant frequencies Technical Paper |
title | Semi-automated impact device based on human behaviour recognition model for in-service modal analysis |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-09T14%3A20%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Semi-automated%20impact%20device%20based%20on%20human%20behaviour%20recognition%20model%20for%20in-service%20modal%20analysis&rft.jtitle=Journal%20of%20the%20Brazilian%20Society%20of%20Mechanical%20Sciences%20and%20Engineering&rft.au=Zahid,%20Fahad%20Bin&rft.date=2023-02-01&rft.volume=45&rft.issue=2&rft.artnum=96&rft.issn=1678-5878&rft.eissn=1806-3691&rft_id=info:doi/10.1007/s40430-023-04022-2&rft_dat=%3Cproquest_cross%3E2766756466%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2766756466&rft_id=info:pmid/&rfr_iscdi=true |