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A fast gas concentration estimation method based on metal-oxide-semiconductor gas sensors

机译:一种基于金属氧化物半导体气体传感器的快气浓度估计方法

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Metal-oxide-semiconductor gas sensors are widely used for gas concentration estimation and identification because of high sensitivity, good robustness and low price. To achieve good estimated performance, the feature extraction method is crucial for gas detection. However, the feature extracted from the transient part of gas response is required for fast gas concentrations estimation. In this paper, we proposed a new transient feature extraction method to reduce the estimated time of gas concentration. The linear regression was utilized to estimate gas concentrations. The result showed the estimation error of gas concentrations was less than 28.6%, and the average completion time was reduced up to 19 times. The proposed method showed superior performance to the conventional features.
机译:金属氧化物 - 半导体气体传感器广泛用于气体浓度估计和识别,因为灵敏度高,稳健性良好和低价格。为了实现良好的估计性能,特征提取方法对于气体检测至关重要。然而,从气体响应的瞬态部分提取的特征是快速气体浓度估计所必需的。在本文中,我们提出了一种新的瞬态特征提取方法,以减少气体浓度的估计时间。线性回归用于估计气体浓度。结果表明,气体浓度的估计误差小于28.6%,平均完成时间减少了高达19次。该方法对传统特征表现出卓越的性能。

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