Dynamic displacement estimation by fusing LDV and LiDAR measurements via smoothing based Kalman filtering

DC FieldValueLanguage
dc.contributor.authorKim, Kiyoung-
dc.contributor.authorSohn, Hoon-
dc.date.accessioned2016-11-09T06:22:46Z-
dc.date.available2016-11-09T06:22:46Z-
dc.date.created2016-06-17-
dc.date.issued2017-01-
dc.identifier.citationMECHANICAL SYSTEMS AND SIGNAL PROCESSING, v.82, no., pp.339 - 355-
dc.identifier.issn0888-3270-
dc.identifier.urihttp://hdl.handle.net/10203/213843-
dc.description.abstractThis paper presents a smoothing based Kalman filter to estimate dynamic displacement in real-time by fusing the velocity measured from a laser Doppler vibrometer (LDV) and the displacement from a light detection and ranging (LiDAR). LiDAR can measure displacement based on the time-of-flight information or the phase-shift of the laser beam reflected off form a target surface, but it typically has a high noise level and a low sampling rate. On the other hand, LDV primarily measures out-of-plane velocity of a moving target, and displacement is estimated by numerical integration of the measured velocity. Here, the displacement estimated by LDV suffers from integration error although LDV can achieve a lower noise level and a much higher sampling rate than LiDAR. The proposed data fusion technique estimates high-precision and high-sampling rate displacement by taking advantage of both LiDAR and LDV measurements and overcomes their limitations by adopting a real-time smoothing based Kalman filter. To verify the performance of the proposed dynamic displacement estimation technique, a series of lab-scale tests are conducted under various loading conditions. (C) 2016 Elsevier Ltd. All rights reserved.-
dc.languageENG-
dc.publisherACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD-
dc.subjectTERRESTRIAL LASER SCANNER-
dc.subjectDOPPLER VIBROMETRY-
dc.subjectSPECKLE NOISE-
dc.subjectTOTAL STATION-
dc.subjectGPS-
dc.subjectDEFLECTIONS-
dc.subjectBRIDGE-
dc.subjectRECONSTRUCTION-
dc.subjectFREQUENCIES-
dc.subjectACCURACY-
dc.titleDynamic displacement estimation by fusing LDV and LiDAR measurements via smoothing based Kalman filtering-
dc.typeArticle-
dc.identifier.wosid000384397500022-
dc.identifier.scopusid2-s2.0-84975126980-
dc.type.rimsART-
dc.citation.volume82-
dc.citation.beginningpage339-
dc.citation.endingpage355-
dc.citation.publicationnameMECHANICAL SYSTEMS AND SIGNAL PROCESSING-
dc.identifier.doi10.1016/j.ymssp.2016.05.027-
dc.contributor.localauthorKim, Kiyoung-
dc.contributor.localauthorSohn, Hoon-
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CE-Journal Papers(저널논문)
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