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dc.contributor.authorBuethe, Inka
dc.contributor.authorTorres-Arredondo, Miguel Angel
dc.contributor.authorMujica Delgado, Luis Eduardo
dc.contributor.authorRodellar Benedé, José
dc.contributor.authorFritzen, Claus-Peter
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Matemàtica Aplicada III
dc.date.accessioned2013-02-26T12:22:01Z
dc.date.available2013-02-26T12:22:01Z
dc.date.created2013
dc.date.issued2013
dc.identifier.citationBuethe, I. [et al.]. Damage detection in piping systems using pattern recognition techniques. A: European Workshop on Structural Health Monitoring. "Proceedings 6th European Workshop on Structural Health Monitoring & 1st European Conference On Prognostics and Health Management, July 3-6, 2012, Dresden, Germany". Dresden: 2013, p. 1-8.
dc.identifier.urihttp://hdl.handle.net/2117/17976
dc.description.abstractThe interest in the propagation of ultrasound waves in pipe-like solid waveguides arises out of several areas of the structural health monitoring (SHM) community for the detection, localization and assessment of defects as well as the prediction of remaining life in civil, mechanical, aeronautic and aerospace structures. SHM premise offers a continuous observation of the structural integrity of operational systems. This is particularly convenient, therefore, for the reduction of time and cost for maintenance without decreasing the level of safety. Some practical applications are the monitoring of pipework in gas and oil industries, suspension bridge cables, nuclear fuel cladding tubes, etc. This paper describes an approach for SHM using guided waves in pipe-like structures in terms of a pattern recognition problem. The formalism is based on a distributed piezoelectric sensor network for the detection of structural dynamic responses. Several methods for signal filtration, feature selection and extraction, and data compression of the recorded time histories are discussed and evaluated. Principal Component Analysis (PCA), Non-Linear PCA (NLPCA) and Wavelet Transform are among them. Additionally, the different clusters, corresponding to each damage level are visualized with the help of Self Organizing Maps (SOM). Tests were performed on a piping system where the properties of the proposed methods are compared and appraised with experimental pitch-catch signals between the pristine and the damaged structure.
dc.format.extent8 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria civil::Materials i estructures
dc.subjectÀrees temàtiques de la UPC::Enginyeria dels materials::Materials compostos
dc.subjectÀrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Aplicacions informàtiques a la física i l‘enginyeria
dc.titleDamage detection in piping systems using pattern recognition techniques
dc.typeConference report
dc.contributor.groupUniversitat Politècnica de Catalunya. CoDAlab - Control, Modelització, Identificació i Aplicacions
dc.rights.accessOpen Access
local.identifier.drac11484820
dc.description.versionPostprint (published version)
local.citation.authorBuethe, I.; Torres-Arredondo, M.; Mujica, L.E.; Rodellar, J.; Fritzen, C.P
local.citation.contributorEuropean Workshop on Structural Health Monitoring
local.citation.pubplaceDresden
local.citation.publicationNameProceedings 6th European Workshop on Structural Health Monitoring & 1st European Conference On Prognostics and Health Management, July 3-6, 2012, Dresden, Germany
local.citation.startingPage1
local.citation.endingPage8


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