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Statistical time energy based damage detection in steel plates using artificial neural networks

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Main Authors: Paulraj, Murugesa Pandiyan, Prof. Madya, Mohd Shukri, Abdul Majid, Sazali, Yaacob, Prof. Dr., Mohd Hafiz, Fazalul Rahiman, Krishnan, R. P.
Format: Working Paper
Language:English
Published: Institute of Electrical and Elctronics Engineering (IEEE) 2010
Subjects:
Back propagation neural network
Damage detection
Time domain
International Colloquium on Signal Processing and Its Applications (CSPA)
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/8651
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spelling my.unimap-86512010-08-13T05:45:32Z Statistical time energy based damage detection in steel plates using artificial neural networks Paulraj, Murugesa Pandiyan, Prof. Madya Mohd Shukri, Abdul Majid Sazali, Yaacob, Prof. Dr. Mohd Hafiz, Fazalul Rahiman Krishnan, R. P. Back propagation neural network Damage detection Time domain International Colloquium on Signal Processing and Its Applications (CSPA) Link to publisher's homepage at http://ieeexplore.ieee.org/ In this paper, a simple method for crack identification in steel plates based on statistical time energy is presented. A simple experimental procedure is also proposed to measure the vibration at different positions of a steel plate. The plate is excited by an impulse signal and made to vibrate; statistical features are then extracted from the vibration signals which are measured at different locations. These features are then used to develop a neural network model. A simple neural network model trained by back propagation algorithm is then developed based on the statistical time energy features to classify the damage location in a steel plate. The effectiveness of the system is validated through simulation. 2010-08-13T05:45:32Z 2010-08-13T05:45:32Z 2009-03-06 Working Paper p.33-36 978-1-4244-4150-1 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5069182 http://hdl.handle.net/123456789/8651 en Proceedings of the 5th International Colloquium on Signal Processing and Its Applications (CSPA) 2009 Institute of Electrical and Elctronics Engineering (IEEE)
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 Back propagation neural network
Damage detection
Time domain
International Colloquium on Signal Processing and Its Applications (CSPA)
spellingShingle Back propagation neural network
Damage detection
Time domain
International Colloquium on Signal Processing and Its Applications (CSPA)
Paulraj, Murugesa Pandiyan, Prof. Madya
Mohd Shukri, Abdul Majid
Sazali, Yaacob, Prof. Dr.
Mohd Hafiz, Fazalul Rahiman
Krishnan, R. P.
Statistical time energy based damage detection in steel plates using artificial neural networks
description Link to publisher's homepage at http://ieeexplore.ieee.org/
format Working Paper
author Paulraj, Murugesa Pandiyan, Prof. Madya
Mohd Shukri, Abdul Majid
Sazali, Yaacob, Prof. Dr.
Mohd Hafiz, Fazalul Rahiman
Krishnan, R. P.
author_facet Paulraj, Murugesa Pandiyan, Prof. Madya
Mohd Shukri, Abdul Majid
Sazali, Yaacob, Prof. Dr.
Mohd Hafiz, Fazalul Rahiman
Krishnan, R. P.
author_sort Paulraj, Murugesa Pandiyan, Prof. Madya
title Statistical time energy based damage detection in steel plates using artificial neural networks
title_short Statistical time energy based damage detection in steel plates using artificial neural networks
title_full Statistical time energy based damage detection in steel plates using artificial neural networks
title_fullStr Statistical time energy based damage detection in steel plates using artificial neural networks
title_full_unstemmed Statistical time energy based damage detection in steel plates using artificial neural networks
title_sort statistical time energy based damage detection in steel plates using artificial neural networks
publisher Institute of Electrical and Elctronics Engineering (IEEE)
publishDate 2010
url http://dspace.unimap.edu.my/xmlui/handle/123456789/8651
_version_ 1643789248429555712
score 13.214268

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