Structural health monitoring using modular wireless sensors

Cited 74 time in webofscience Cited 0 time in scopus
  • Hit : 312
  • Download : 649
DC FieldValueLanguage
dc.contributor.authorTanner, NAko
dc.contributor.authorWait, JRko
dc.contributor.authorFarrar, CRko
dc.contributor.authorSohn, Hoonko
dc.date.accessioned2010-06-10T05:20:28Z-
dc.date.available2010-06-10T05:20:28Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2003-01-
dc.identifier.citationJOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES, v.14, no.1, pp.43 - 56-
dc.identifier.issn1045-389X-
dc.identifier.urihttp://hdl.handle.net/10203/18811-
dc.description.abstractSystem integration of an online structural health monitoring module was accomplished by coupling commercially available microclectro-mechanical system sensors and a wireless telemetry unit with damage detection firmware. To showcase the capabilities of the integrated monitoring module, a bolted frame structure was constructed, and the preload in one of the bolted joints was controlled by a piezoelectric stack actuator to simulate gradual deterioration of a bolted connection. Two separate damage detection algorithms were used to classify a joint as damaged or undamaged. First, a statistical process control algorithm was used to monitor the correlation of vibration data from two accelerometers mounted across a joint. Changes in correlation were used to detect damage to the joint. For each joint, data were processed locally on a microprocessor integrated with the wireless module, and the diagnosis result was remotely transmitted to the base monitoring station. Second, a more sophisticated damage detection algorithm combining time series analysis and statistical hypothesis testing was employed using a conventional wired data acquisition system to classify a joint on the demonstration structure as damaged or undamaged.-
dc.description.sponsorshipFunding for this project was provided by the Department ofEnergy through the internal funding program at Los Alamos National Laboratory known as Laboratory Directed Research and Development. The first author, Neal A. Tanner, was supported by a fellowship from the Fannie and John Hertz Foundation. The authors would also like to acknowledge Jason Hill in the Computer Science Department at the University of California, Berkeley for his consultation regarding programming ofthe motes. Finally, the authors acknowledge the contribution ofCrossb ow, Inc. in San Jose, CA for providing the Mote hardware.en
dc.languageEnglish-
dc.language.isoen_USen
dc.publisherSAGE PUBLICATIONS LTD-
dc.titleStructural health monitoring using modular wireless sensors-
dc.typeArticle-
dc.identifier.wosid000183783100005-
dc.identifier.scopusid2-s2.0-0042849259-
dc.type.rimsART-
dc.citation.volume14-
dc.citation.issue1-
dc.citation.beginningpage43-
dc.citation.endingpage56-
dc.citation.publicationnameJOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES-
dc.identifier.doi10.1177/104538903033641-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorSohn, Hoon-
dc.contributor.nonIdAuthorTanner, NA-
dc.contributor.nonIdAuthorWait, JR-
dc.contributor.nonIdAuthorFarrar, CR-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorstructural health monitoring-
dc.subject.keywordAuthorwireless sensor module-
dc.subject.keywordAuthorremote sensing-
dc.subject.keywordAuthorreal-time damage detection-
dc.subject.keywordAuthorstatistical process control-
dc.subject.keywordAuthorstatistical pattern recognition-
dc.subject.keywordAuthorand time series analysis-
Appears in Collection
CE-Journal Papers(저널논문)
Files in This Item
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 74 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0