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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/14045

Title: Classifying material type and mechanical properties using artificial neural network
Authors: Intan Maisarah, Abd Rahim
Fauziah, Mat
Sazali, Yaacob, Prof. Dr.
Rakhmad Arief, Siregar
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Keywords: Frequency Response Function;Levenberg-Marquardt Backpropagation;Vibration analysis;Vibration technique
Issue Date: 4-Mar-2011
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: p. 207-211
Series/Report no.: Proceedings of the 7th International Colloquium on Signal Processing and its Applications (CSPA 2011)
Abstract: This paper focused on experimental data and study for the testing of the material mechanical properties using vibration technique. By applying vibration analysis and testing on the material, we could determine the natural frequencies, the damping ratio and mode shapes of the structure. However, in this study, we only considering the natural frequencies of the material as the input data needed for training. As an extension for the study, the system tested with various method of neural network training algorithm. The Levenberg-Marquardt Backpropagation used as the algorithm in an artificial neural network system developed
Description: Link to publisher's homepage at http://ieeexplore.ieee.org/
URI: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5759874
ISBN: 978-161284414-5
Appears in Collections:Rakhmad Arief Siregar, Dr.
Conference Papers
Sazali Yaacob, Prof. Dr.

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