@ARTICLE{Gwiżdż_Patryk_Hydrogen_2015,
 author={Gwiżdż, Patryk and Brudnik, Andrzej and Zakrzewska, Katarzyna},
 volume={vol. 22},
 number={No 1},
 journal={Metrology and Measurement Systems},
 pages={3-12},
 howpublished={online},
 year={2015},
 publisher={Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation},
 abstract={An array consisting of four commercial gas sensors with target specifications for hydrocarbons, ammonia, alcohol, explosive gases has been constructed and tested. The sensors in the array operate in the dynamic mode upon the temperature modulation from 350°C to 500°C. Changes in the sensor operating temperature lead to distinct resistance responses affected by the gas type, its concentration and the humidity level. The measurements are performed upon various hydrogen (17-3000 ppm), methane (167-3000 ppm) and propane (167-3000 ppm) concentrations at relative humidity levels of 0-75%RH. The measured dynamic response signals are further processed with the Discrete Fourier Transform. Absolute values of the dc component and the first five harmonics of each sensor are analysed by a feed-forward back-propagation neural network. The ultimate aim of this research is to achieve a reliable hydrogen detection despite an interference of the humidity and residual gases.},
 title={Hydrogen Detection With a Gas Sensor Array – Processing and Recognition of Dynamic Responses Using Neural Networks},
 URL={http://journals.pan.pl/Content/90296/PDF/Journal10178-VolumeXXII%20Issue1_01.pdf},
 doi={10.1515/mms-2015-0008},
 keywords={gas sensor, sensor array, temperature modulation, dynamic response, feature extraction, neural networks},
}