Title :
A Technique for Detecting Materials Characteristics using Mechanical Impacts and a Multilayer Neural Network
Author :
Molino-Minero-Re, Erik ; Lopez-Garcia, Mariano ; Manuel-Lazaro, Antoni ; Carlosena, Alfonso ; Shariat-Panahi, Shahram
Author_Institution :
Polytech. Univ. of Catalonia, Vilanova i la Geltru
Abstract :
In this paper, we propose a method for detecting the characteristics of different materials that have similar properties, by classifying their responses when impacted with small hard spheres. First, a signal conditioning and data compression stage are described. Then a multilayer neural network is used to detect the individual patterns of the samples, and classify the signal. The results of this study indicate that it is possible to identify different materials propertied when the signals are correctly acquired and preprocessed, and the network is adequately trained.
Keywords :
data compression; impact (mechanical); learning (artificial intelligence); mechanical engineering computing; data compression stage; mechanical impacts; multilayer neural network; Acceleration; Accelerometers; Artificial neural networks; Electric shock; Multi-layer neural network; Neural networks; Signal analysis; Signal generators; Testing; Transient analysis; Impacts; materials characteristics; multilayer neural networks; piezoelectric accelerometer;
Conference_Titel :
Instrumentation and Measurement Technology Conference Proceedings, 2008. IMTC 2008. IEEE
Conference_Location :
Victoria, BC
Print_ISBN :
978-1-4244-1540-3
Electronic_ISBN :
1091-5281
DOI :
10.1109/IMTC.2008.4547217
