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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/dspace/handle/123456789/8647

Title: Damage detection in steel plates using artificial neural networks
Authors: Paulraj, Murugesa Pandiyan, Prof. Madya
Mohd Shukri, Abdul Majid
Sazali, Yaacob, Prof. Dr.
Mohd Hafiz, Fazalul Rahiman
Krishnan, R. P.
Keywords: Back propagation neural network;Damage detection;Discrete cosine transformation;Time domain;International Conference Control, Automation, Communication and Energy Conservation (INCACEC)
Issue Date: 4-Jun-2009
Publisher: Institute of Electrical and Electronics Engineering (IEEE)
Citation: p.1-4
Series/Report no.: Proceedings of the International Conference on Control Automation, Communication and Energy Conservation (INCACEC) 2009
Abstract: In this paper, a simple method for crack identification in steel plates based on frame energy based Discrete Cosine Transformation (DCT) is presented. A simple experimental procedure is also proposed to measure the vibration at different positions of the steel plate. The plate is excited by an impulse signal and made to vibrate. Energy based DCT features are then extracted from the vibration signals which are measured at different locations. A simple neural network model is developed, trained by Back Propagation (BP), to associate the frame energy based DCT features with the damage or undamaged locations of the steel plate. The effectiveness of the system is validated through simulation.
Description: Link to publisher's homepage at http://ieeexplore.ieee.org/
URI: http://ieeexplore.ieee.org/search/srchabstract.jsp?tp=&arnumber=5204365&queryText%3D%28Document+Title%3ADamage+detection+in+steel+plates+using+artificial+neural+networks%29%26openedRefinements%3D*%26matchBoolean%3Dtrue%26searchField%3DSearch+All
http://hdl.handle.net/123456789/8647
ISBN: 978-1-4244-4789-3
Appears in Collections:Paulraj Murugesa Pandiyan, Prof. Dr.
Conference Papers
Sazali Yaacob, Prof. Dr.

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