Analysing method for acoustic emission clustering system on reinforced concrete beam

Acoustic Emission (AE) is a non-destructive testing (NDT) method used for damage detection in structural engineering. Nowadays, NDT is widely used especially on continuous real-time monitoring systems with minimum labour involvement. It could also be used to discriminate the different types of damag...

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Main Author: Saiful Bahari, Nur Amira Afiza
Format: Thesis
Language:English
English
English
Published: 2018
Subjects:
Online Access:http://eprints.uthm.edu.my/355/
http://eprints.uthm.edu.my/355/1/24p%20NUR%20AMIRA%20AFIZA%20SAIFUL%20BAHARI.pdf
http://eprints.uthm.edu.my/355/2/NUR%20AMIRA%20AFIZA%20SAIFUL%20BAHARI%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/355/3/NUR%20AMIRA%20AFIZA%20SAIFUL%20BAHARI%20WATERMARK.pdf
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author Saiful Bahari, Nur Amira Afiza
author_facet Saiful Bahari, Nur Amira Afiza
author_sort Saiful Bahari, Nur Amira Afiza
building UTHM Institutional Repository
collection Online Access
description Acoustic Emission (AE) is a non-destructive testing (NDT) method used for damage detection in structural engineering. Nowadays, NDT is widely used especially on continuous real-time monitoring systems with minimum labour involvement. It could also be used to discriminate the different types of damage occurring in reinforced concrete (RC) beam. In spite of these advantages, difficulties still exist in using the AE technique for monitoring applications particularly in analysing recorded AE data due to the large quantity of data involved. Other than that, the main problem associated with data analysis is the discrimination between different AE sources and the analysis of AE signals in order to identify the most critical damage mechanism. Clustering analysis is a technique in which a set of objects are assigned to a group called cluster. The need for effective data analysis in the clustering system can be linked to three main objectives in this research; (1) to determine the type of failure on reinforced concrete beams through the AE system; (2) to identify and discriminate the AE data parameters via crack classification (tensile and shear movement); (3) to verify the crack classification of Rise Amplitude (RA) clustering by using the NI LabVIEW clustering algorithm. Hence, the purpose of this research is to obtain the crack classification by using the RA clustering analysing (RAC) method. It was found that, the result by using RAC analysing method was reliable system to cluster the cracking on RC beam. In addition, these analysing system could use in any different sizing of beam.
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format Thesis
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institution Universiti Tun Hussein Onn Malaysia
institution_category Local University
language English
English
English
last_indexed 2025-11-15T19:50:08Z
publishDate 2018
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spelling uthm-3552021-07-25T00:58:25Z http://eprints.uthm.edu.my/355/ Analysing method for acoustic emission clustering system on reinforced concrete beam Saiful Bahari, Nur Amira Afiza TA401-492 Materials of engineering and construction. Mechanics of materials Acoustic Emission (AE) is a non-destructive testing (NDT) method used for damage detection in structural engineering. Nowadays, NDT is widely used especially on continuous real-time monitoring systems with minimum labour involvement. It could also be used to discriminate the different types of damage occurring in reinforced concrete (RC) beam. In spite of these advantages, difficulties still exist in using the AE technique for monitoring applications particularly in analysing recorded AE data due to the large quantity of data involved. Other than that, the main problem associated with data analysis is the discrimination between different AE sources and the analysis of AE signals in order to identify the most critical damage mechanism. Clustering analysis is a technique in which a set of objects are assigned to a group called cluster. The need for effective data analysis in the clustering system can be linked to three main objectives in this research; (1) to determine the type of failure on reinforced concrete beams through the AE system; (2) to identify and discriminate the AE data parameters via crack classification (tensile and shear movement); (3) to verify the crack classification of Rise Amplitude (RA) clustering by using the NI LabVIEW clustering algorithm. Hence, the purpose of this research is to obtain the crack classification by using the RA clustering analysing (RAC) method. It was found that, the result by using RAC analysing method was reliable system to cluster the cracking on RC beam. In addition, these analysing system could use in any different sizing of beam. 2018 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/355/1/24p%20NUR%20AMIRA%20AFIZA%20SAIFUL%20BAHARI.pdf text en http://eprints.uthm.edu.my/355/2/NUR%20AMIRA%20AFIZA%20SAIFUL%20BAHARI%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/355/3/NUR%20AMIRA%20AFIZA%20SAIFUL%20BAHARI%20WATERMARK.pdf Saiful Bahari, Nur Amira Afiza (2018) Analysing method for acoustic emission clustering system on reinforced concrete beam. Masters thesis, Universiti Tun Hussein Onn Malaysia.
spellingShingle TA401-492 Materials of engineering and construction. Mechanics of materials
Saiful Bahari, Nur Amira Afiza
Analysing method for acoustic emission clustering system on reinforced concrete beam
title Analysing method for acoustic emission clustering system on reinforced concrete beam
title_full Analysing method for acoustic emission clustering system on reinforced concrete beam
title_fullStr Analysing method for acoustic emission clustering system on reinforced concrete beam
title_full_unstemmed Analysing method for acoustic emission clustering system on reinforced concrete beam
title_short Analysing method for acoustic emission clustering system on reinforced concrete beam
title_sort analysing method for acoustic emission clustering system on reinforced concrete beam
topic TA401-492 Materials of engineering and construction. Mechanics of materials
url http://eprints.uthm.edu.my/355/
http://eprints.uthm.edu.my/355/1/24p%20NUR%20AMIRA%20AFIZA%20SAIFUL%20BAHARI.pdf
http://eprints.uthm.edu.my/355/2/NUR%20AMIRA%20AFIZA%20SAIFUL%20BAHARI%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/355/3/NUR%20AMIRA%20AFIZA%20SAIFUL%20BAHARI%20WATERMARK.pdf