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首页> 外文期刊>Metrology and Measurement Systems: Metrologia i Systemy Pomiarowe >DETERMINATION OF GAS MIXTURE COMPONENTS USING FLUCTUATION ENHANCED SENSING AND THE LS-SVM REGRESSION ALGORITHM
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DETERMINATION OF GAS MIXTURE COMPONENTS USING FLUCTUATION ENHANCED SENSING AND THE LS-SVM REGRESSION ALGORITHM

机译:使用波动增强感测的气体混合物组分和LS-SVM回归算法的测定

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摘要

This paper analyses the effectiveness of determining gas concentrations by using a prototype WO3 resistive gas sensor together with fluctuation enhanced sensing. We have earlier demonstrated that this method can determine the composition of a gas mixture by using only a single sensor. In the present study, we apply Least-Squares Support-Vector-Machine-based (LS-SVM-based) nonlinear regression to determine the gas concentration of each constituent in a mixture. We confirmed that the accuracy of the estimated gas concentration could be significantly improved by applying temperature change and ultraviolet irradiation of the WO3 layer. Fluctuation-enhanced sensing allowed us to predict the concentration of both component gases.
机译:本文分析了通过使用原型WO3电阻气体传感器与波动增强感测来确定气体浓度的有效性。我们早先说明该方法可以通过仅使用单个传感器来确定气体混合物的组成。在本研究中,我们应用最小二乘支持 - 向量 - 载体机基(基于LS-SVM的)非线性回归,以确定混合物中各组分的气体浓度。我们证实,通过施加温度变化和WO3层的紫外线照射,可以显着提高估计气体浓度的准确性。波动增强的感测使我们能够预测两种组分气体的浓度。

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