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Classification of chemical systems using acoustic emission and neural networks
Journal article

Classification of chemical systems using acoustic emission and neural networks

Ryszard Lec, Peter Lewin, Sun Kwoun and Emil Radulescu
Proceedings of the First Joint BMES/EMBS Conference : serving humanity advancing technology, Oct. 13-16, 99, Atlanta, GA, USA, v 2, pp 811-811
01 Jan 1999

Abstract

Acoustic emissions Chemical sensors Microsensors Neural networks Ultrasonic transducers Probability
A novel acoustic wave sensor capable of classification of chemical reactions has been designed, fabricated and tested. The principle of sensor operation is based on the acoustic emission phenomena. The acoustic emission chemical (AEC) sensor consists of four sections: the measurement cell with ultrasonic transducers operating in the frequency range from 90 kHz to 2 MHz, the frequency domain signal detection unit, the signal processing unit based on a neural network and a computer controlled data acquisition system.

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