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Structural steel plate damage detection using non destructive testing, frame energy based statistical features and artificial neural networks

Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2012 organised by technical universities under the Malaysian Technical Universities Network (MTUN), 20th - 21st November 2012 at Hotel Seri Malaysia, Kangar, Perlis.

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Bibliographic Details
Main Authors: Paulraj, Murugesa Pandiyan, Dr., Sazali, Yaacob, Prof. Dr., Mohd Shukry, Abdul Majid, Mohd Nor Fakhzan, Mohd Kazim, Pranesh, Krishnan
Other Authors: paul@unimap.edu.my
Format: Working Paper
Language:English
Published: Malaysian Technical Universities Network (MTUN) 2013
Subjects:
Non destructive testing
Feed-forward neural network
Vibration signals
Frame energy based statistical features
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/26997
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spelling my.unimap-269972013-07-23T07:12:38Z Structural steel plate damage detection using non destructive testing, frame energy based statistical features and artificial neural networks Paulraj, Murugesa Pandiyan, Dr. Sazali, Yaacob, Prof. Dr. Mohd Shukry, Abdul Majid Mohd Nor Fakhzan, Mohd Kazim Pranesh, Krishnan paul@unimap.edu.my Non destructive testing Feed-forward neural network Vibration signals Frame energy based statistical features Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2012 organised by technical universities under the Malaysian Technical Universities Network (MTUN), 20th - 21st November 2012 at Hotel Seri Malaysia, Kangar, Perlis. This paper discusses about the detection of damages present in the steel plates using nondestructive vibration testing. A simple experimental model has been developed to hold the steel plate complying with the simply supported boundary condition. Vibration patterns from the steel structure are captured based on the impact testing using a simple protocol. The vibration signals in normal condition of the steel plate are recorded. The damages of size 512 |x m to 1852 |j, m are simulated manually on the steel plate using drill bits. The vibration signals in the fault condition of the steel plate are collected. The captured vibration signals are preprocessed and time domain based feature extraction algorithms are developed to extract features from the vibration signals. The conditions of the steel plate namely healthy and faulty are associated with the extracted features to establish input output mapping. A feed-forward neural network is modeled to classify the condition. The neural network parameters are adjusted to train the network. The performance of the network is calculated using Falhman criterion. 2013-07-23T07:12:38Z 2013-07-23T07:12:38Z 2012-11-20 Working Paper p. 137-144 http://hdl.handle.net/123456789/26997 en Proceedings of the Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2012 Malaysian Technical Universities Network (MTUN)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Non destructive testing
Feed-forward neural network
Vibration signals
Frame energy based statistical features
spellingShingle Non destructive testing
Feed-forward neural network
Vibration signals
Frame energy based statistical features
Paulraj, Murugesa Pandiyan, Dr.
Sazali, Yaacob, Prof. Dr.
Mohd Shukry, Abdul Majid
Mohd Nor Fakhzan, Mohd Kazim
Pranesh, Krishnan
Structural steel plate damage detection using non destructive testing, frame energy based statistical features and artificial neural networks
description Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2012 organised by technical universities under the Malaysian Technical Universities Network (MTUN), 20th - 21st November 2012 at Hotel Seri Malaysia, Kangar, Perlis.
author2 paul@unimap.edu.my
author_facet paul@unimap.edu.my
Paulraj, Murugesa Pandiyan, Dr.
Sazali, Yaacob, Prof. Dr.
Mohd Shukry, Abdul Majid
Mohd Nor Fakhzan, Mohd Kazim
Pranesh, Krishnan
format Working Paper
author Paulraj, Murugesa Pandiyan, Dr.
Sazali, Yaacob, Prof. Dr.
Mohd Shukry, Abdul Majid
Mohd Nor Fakhzan, Mohd Kazim
Pranesh, Krishnan
author_sort Paulraj, Murugesa Pandiyan, Dr.
title Structural steel plate damage detection using non destructive testing, frame energy based statistical features and artificial neural networks
title_short Structural steel plate damage detection using non destructive testing, frame energy based statistical features and artificial neural networks
title_full Structural steel plate damage detection using non destructive testing, frame energy based statistical features and artificial neural networks
title_fullStr Structural steel plate damage detection using non destructive testing, frame energy based statistical features and artificial neural networks
title_full_unstemmed Structural steel plate damage detection using non destructive testing, frame energy based statistical features and artificial neural networks
title_sort structural steel plate damage detection using non destructive testing, frame energy based statistical features and artificial neural networks
publisher Malaysian Technical Universities Network (MTUN)
publishDate 2013
url http://dspace.unimap.edu.my/xmlui/handle/123456789/26997
_version_ 1643795017015230464
score 13.214268

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