Title :
Neural network-based waveguide acoustic gas detector
Author :
Alsabbah, Shebel ; Mughrabi, Tariq
Author_Institution :
Dept. of Mechatron., Al Balqa Appl. Univ., Amman
Abstract :
At present, gas chromatography is a universal technique used for analysis. The technical features of gas chromatographs are determined by the properties of gas detectors. One of the most recent and perspective gas detectors is the waveguide acoustic detector, in which chromatogram represents the mass concentration of the gas to be detected. With MATLAB computational language and iteration algorithm, a neural network-based waveguide detector is proposed, to predict the frequency and mass concentration of the unknown gas (sample). Experimental data has been chosen to create the database of the neural network-based detector. The proposed model has been tested and validated numerically with results.
Keywords :
chemical engineering computing; chromatography; gas sensors; neural nets; computational language; gas chromatography; iteration algorithm; neural network; waveguide acoustic gas detector; Acoustic signal detection; Acoustic waveguides; Acoustic waves; Computer networks; Databases; Frequency; Gas chromatography; Gas detectors; MATLAB; Neural networks;
Conference_Titel :
Mechatronics and Its Applications, 2008. ISMA 2008. 5th International Symposium on
Conference_Location :
Amman
Print_ISBN :
978-1-4244-2033-9
Electronic_ISBN :
978-1-4244-2034-6
DOI :
10.1109/ISMA.2008.4648867