Features of Hardware and Software Smoothing of Experimental Data of Gas Sensors

When conducting experimental studies, numerical values of quantities are often recorded, which are often measured with some error associated not only with the measurement technique, the error measurement of instruments, but also with the presence of noise. In this regard, the natural desire of resea...

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Bibliographic Details
Published in:2021 IEEE International Conference on Smart Information Systems and Technologies (SIST) pp. 1 - 6
Main Authors: Mukanova, Zhanna, Atanov, Sabyrzhan, Jamshidi, Mohammad
Format: Conference Proceeding
Language:English
Published: IEEE 28.04.2021
Subjects:
Approximation algorithms
curve smoothing
data
data smoothing algorithms software application
gas analyzer
Hardware
Low-pass filters
Measurement uncertainty
signal
Smoothing methods
Software
Software algorithms
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Summary:When conducting experimental studies, numerical values of quantities are often recorded, which are often measured with some error associated not only with the measurement technique, the error measurement of instruments, but also with the presence of noise. In this regard, the natural desire of researchers to minimize measurement errors and noise is understandable. To solve this problem, when processing experimental data, it is necessary to use the approximation of the results, i.e. smoothing the curve data. This article provides a comparative analysis of some of the most effective smoothing algorithms based on data obtained experimentally using a laboratory benchmark with removable sensors MQ-135 and ME2-O2-F20. The application of smoothing algorithms was implemented using the software application SCA (Smoothing Curve Application) which allowed to cancel hardware measurement noise.
DOI:10.1109/SIST50301.2021.9465981