Damage classification of pipelines under water flow operation using multi-mode actuated sensing technology
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, C[Lee, Changgil] | - |
dc.contributor.author | Park, S[Park, Seunghee] | - |
dc.date.accessioned | 2021-08-05T19:49:59Z | - |
dc.date.available | 2021-08-05T19:49:59Z | - |
dc.date.created | 2016-08-06 | - |
dc.date.issued | 2011-11 | - |
dc.identifier.issn | 0964-1726 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/skku/handle/2021.sw.skku/68490 | - |
dc.description.abstract | In a structure, several types of damage can occur, ranging from micro-cracking to corrosion or loose bolts. This makes identifying the damage difficult with a single mode of sensing. Therefore, a multi-mode actuated sensing system is proposed based on a self-sensing circuit using a piezoelectric sensor. In self-sensing-based multi-mode actuated sensing, one mode provides a wide frequency-band structural response from the self-sensed impedance measurement and the other mode provides a specific frequency-induced structural wavelet response from the self-sensed guided wave measurement. In this experimental study, a pipeline system under water flow operation was examined to verify the effectiveness and robustness of the proposed structural health monitoring approach. Different types of structural damage were inflicted artificially on the pipeline system. To classify the multiple types of structural damage, supervised learning-based statistical pattern recognition was implemented by composing a three-dimensional space using the damage indices extracted from the impedance and guided wave features as well as temperature variations. For a more systematic damage classification, several control parameters were optimized to determine an optimal decision boundary for the supervised learning-based pattern recognition. Further research issues are also discussed for real-world implementations of the proposed approach. | - |
dc.title | Damage classification of pipelines under water flow operation using multi-mode actuated sensing technology | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, C[Lee, Changgil] | - |
dc.contributor.affiliatedAuthor | Park, S[Park, Seunghee] | - |
dc.identifier.doi | 10.1088/0964-1726/20/11/115002 | - |
dc.identifier.scopusid | 2-s2.0-80155182098 | - |
dc.identifier.wosid | 000296922400002 | - |
dc.identifier.bibliographicCitation | SMART MATERIALS & STRUCTURES, v.20, no.11 | - |
dc.relation.isPartOf | SMART MATERIALS & STRUCTURES | - |
dc.citation.title | SMART MATERIALS & STRUCTURES | - |
dc.citation.volume | 20 | - |
dc.citation.number | 11 | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(03063) 25-2, SUNGKYUNKWAN-RO, JONGNO-GU, SEOUL, KOREAsamsunglib@skku.edu
COPYRIGHT © 2021 SUNGKYUNKWAN UNIVERSITY ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.