Damage detection in frame structures using noisy accelerometers and Damage Load Vectors (DLV)

In the domain of damage detection, many notable methods have been introduced over the past years. Damage Load Vectors (DLV) is among the most powerful methods, which computes a set of load vectors from variations in exibility matrices of a frame in undamaged and damaged conditions. These exibility m...

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Main Authors: Toloue, I., Liew, M.S., Hamonangan Harahap, I.S., Lee, H.E.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.23070 /
Published: Sharif University of Technology 2020
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099850293&doi=10.24200%2fsci.2018.50533.1741&partnerID=40&md5=d530cf761984f737daeaa855d508f67a
http://eprints.utp.edu.my/23070/
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spelling utp-eprints.230702021-08-19T05:27:39Z Damage detection in frame structures using noisy accelerometers and Damage Load Vectors (DLV) Toloue, I. Liew, M.S. Hamonangan Harahap, I.S. Lee, H.E. In the domain of damage detection, many notable methods have been introduced over the past years. Damage Load Vectors (DLV) is among the most powerful methods, which computes a set of load vectors from variations in exibility matrices of a frame in undamaged and damaged conditions. These exibility matrices are derived from acceleration responses of the frame that can be captured using accelerometers. The DLV method then scrutinizes this shift among exibility matrices, which ultimately enables locating the damaged member(s). This study holistically conducted seven experimental tests with seven damage scenarios of a test frame installed on a semi-harmonic shaking table. The DLV method was subsequently employed to locate the damaged members using recorded frame vibration data that were obtained from 'noisy' accelerometers positioned on the frame at eight predefined locations. The Eigen Realization Algorithm (ERA) alongside Pandy's recommendations was adopted herein to facilitate the generation of accurate exibility matrices derived from the noisy accelerometers. The outcome is very encouraging with the accurate identification of damaged members in all seven damage scenarios without any 'positive-false' and 'negative-false' findings. Additionally, there is a decrease (from 0.045 to 0.289) in the accuracy of Weighted Stress Indices (WSI) index when the number of damaged members is increased. © 2020 Sharif University of Technology. Sharif University of Technology 2020 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099850293&doi=10.24200%2fsci.2018.50533.1741&partnerID=40&md5=d530cf761984f737daeaa855d508f67a Toloue, I. and Liew, M.S. and Hamonangan Harahap, I.S. and Lee, H.E. (2020) Damage detection in frame structures using noisy accelerometers and Damage Load Vectors (DLV). Scientia Iranica, 27 (4 A). pp. 1776-1785. http://eprints.utp.edu.my/23070/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description In the domain of damage detection, many notable methods have been introduced over the past years. Damage Load Vectors (DLV) is among the most powerful methods, which computes a set of load vectors from variations in exibility matrices of a frame in undamaged and damaged conditions. These exibility matrices are derived from acceleration responses of the frame that can be captured using accelerometers. The DLV method then scrutinizes this shift among exibility matrices, which ultimately enables locating the damaged member(s). This study holistically conducted seven experimental tests with seven damage scenarios of a test frame installed on a semi-harmonic shaking table. The DLV method was subsequently employed to locate the damaged members using recorded frame vibration data that were obtained from 'noisy' accelerometers positioned on the frame at eight predefined locations. The Eigen Realization Algorithm (ERA) alongside Pandy's recommendations was adopted herein to facilitate the generation of accurate exibility matrices derived from the noisy accelerometers. The outcome is very encouraging with the accurate identification of damaged members in all seven damage scenarios without any 'positive-false' and 'negative-false' findings. Additionally, there is a decrease (from 0.045 to 0.289) in the accuracy of Weighted Stress Indices (WSI) index when the number of damaged members is increased. © 2020 Sharif University of Technology.
format Article
author Toloue, I.
Liew, M.S.
Hamonangan Harahap, I.S.
Lee, H.E.
spellingShingle Toloue, I.
Liew, M.S.
Hamonangan Harahap, I.S.
Lee, H.E.
Damage detection in frame structures using noisy accelerometers and Damage Load Vectors (DLV)
author_sort Toloue, I.
title Damage detection in frame structures using noisy accelerometers and Damage Load Vectors (DLV)
title_short Damage detection in frame structures using noisy accelerometers and Damage Load Vectors (DLV)
title_full Damage detection in frame structures using noisy accelerometers and Damage Load Vectors (DLV)
title_fullStr Damage detection in frame structures using noisy accelerometers and Damage Load Vectors (DLV)
title_full_unstemmed Damage detection in frame structures using noisy accelerometers and Damage Load Vectors (DLV)
title_sort damage detection in frame structures using noisy accelerometers and damage load vectors (dlv)
publisher Sharif University of Technology
publishDate 2020
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099850293&doi=10.24200%2fsci.2018.50533.1741&partnerID=40&md5=d530cf761984f737daeaa855d508f67a
http://eprints.utp.edu.my/23070/
_version_ 1741196615826276352
score 11.62408

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