Title :
Classifying material type and mechanical properties using artificial neural network
Author :
Rahim, Intan Maisarah Abd ; Mat, Fauziah ; Yaacob, Sazali ; Siregar, Rakhmad Arief
Author_Institution :
Sch. of Mechatron., Univ. Malaysia Perlis, Kuala Perlis, Malaysia
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.
Keywords :
backpropagation; damping; materials science computing; mechanical properties; neural nets; vibrations; Levenberg-Marquardt backpropagation; artificial neural network; damping ratio; material mechanical property testing; material type classification; mode shape; neural network training algorithm; vibration analysis; Artificial neural networks; Materials; Modal analysis; Signal processing algorithms; Training; Vibrations; Frequency Response Function; Levenberg-Marquardt Backpropagation; vibration analysis; vibration technique;
Conference_Titel :
Signal Processing and its Applications (CSPA), 2011 IEEE 7th International Colloquium on
Conference_Location :
Penang
Print_ISBN :
978-1-61284-414-5
DOI :
10.1109/CSPA.2011.5759874