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Role of sensors in error propagation with the dynamic constrained observability method
dc.contributor.author | Peng, Tian |
dc.contributor.author | Nogal Macho, María |
dc.contributor.author | Casas Rius, Joan Ramon |
dc.contributor.author | Turmo Coderque, José |
dc.contributor.other | Universitat Politècnica de Catalunya. Doctorat en Enginyeria de la Construcció |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental |
dc.date.accessioned | 2021-04-26T13:08:09Z |
dc.date.available | 2021-04-26T13:08:09Z |
dc.date.issued | 2021-05 |
dc.identifier.citation | Peng, T. [et al.]. Role of sensors in error propagation with the dynamic constrained observability method. "Sensors", Maig 2021, vol. 21, núm. 9, p. 2918:1-2918:21. |
dc.identifier.issn | 1424-8220 |
dc.identifier.uri | http://hdl.handle.net/2117/344405 |
dc.description.abstract | The inverse problem of structural system identification is prone to ill-conditioning issues; thus, uniqueness and stability cannot be guaranteed. This issue tends to amplify the error propagation of both the epistemic and aleatory uncertainties, where aleatory uncertainty is related to the accuracy and the quality of sensors. The analysis of uncertainty quantification (UQ) is necessary to assess the effect of uncertainties on the estimated parameters. A literature review is conducted in this paper to check the state of existing approaches for efficient UQ in the parameter identification field. It is identified that the proposed dynamic constrained observability method (COM) can make up for some of the shortcomings of existing methods. After that, the COM is used to analyze a real bridge. The result is compared with the existing method, demonstrating its applicability and correct performance by a reinforced concrete beam. In addition, during the bridge system identification by COM, it is found that the best measurement set in terms of the range will depend on whether the epistemic uncertainty involved or not. It is concluded that, because the epistemic uncertainty will be removed as the knowledge of the structure increases, the optimum sensor placement should be achieved considering not only the accuracy of sensors, but also the unknown structural part. |
dc.description.sponsorship | This research work was conducted with financial support from the Chinese Scholarship Council and the Spanish Ministry of Economy and Competitiveness and FEDER funds (BIA2017-86811-C2-1-R). Authors are also indebted to the Secretaria d’ Universitats i Recerca de la Generalitat de Catalunya for the funding provided through Agaur (2017 SGR 1481). |
dc.language.iso | eng |
dc.publisher | Multidisciplinary Digital Publishing Institute (MDPI) |
dc.rights | Attribution 3.0 Spain |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures |
dc.subject.lcsh | Structural health monitoring |
dc.subject.lcsh | Optical fiber detectors |
dc.subject.other | System identification |
dc.subject.other | Uncertainty quantification |
dc.subject.other | Observability |
dc.subject.other | Frequencies |
dc.subject.other | Mode Shapes |
dc.subject.other | Epistemic uncertainty |
dc.subject.other | Aleatory uncertainty |
dc.subject.other | Sensors |
dc.title | Role of sensors in error propagation with the dynamic constrained observability method |
dc.type | Article |
dc.subject.lemac | Monitorització de salut estructural |
dc.subject.lemac | Detectors de fibra òptica |
dc.contributor.group | Universitat Politècnica de Catalunya. EC - Enginyeria de la Construcció |
dc.identifier.doi | 10.3390/s21092918 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | https://www.mdpi.com/1424-8220/21/9/2918/htm |
dc.rights.access | Open Access |
local.identifier.drac | 31217590 |
dc.description.version | Postprint (published version) |
dc.relation.projectid | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/BIA2017-86811-C2-1-R/ES/MODELOS ESTRUCTURALES PARA LA GESTION EFICIENTE DE INFRAESTRUCTURAS: SMART BIM MODELS/ |
local.citation.author | Peng, T.; Nogal, M.; Casas, J.; Turmo, J. |
local.citation.publicationName | Sensors |
local.citation.volume | 21 |
local.citation.number | 9 |
local.citation.startingPage | 2918:1 |
local.citation.endingPage | 2918:21 |
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