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Features extraction from the electrocatalytic gas sensor responses

机译:从电催化气体传感器响应中提取特征

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摘要

One of the types of gas sensors used for detection and identification of toxic-air pollutant is an electrocatalytic gas sensor. The electrocatalytic sensors are working in cyclic voltammetry mode, enable detection of various gases. Their response are in the form of Ⅰ-Ⅴ curves which contain information about the type and the concentration of measured volatile compound. However, additional analysis is required to provide the efficient recognition of the target gas. Multivariate data analysis and pattern recognition methods are proven to be useful tool for such application, but further investigations on the improvement of the sensor's responses processing are required. In this article the method for extraction of the parameters from the electrocatalytic sensor responses is presented. Extracted features enable the significant reduction of data dimension without the loss of the efficiency of recognition of four volatile air-pollutant, namely nitrogen dioxide, ammonia, hydrogen sulfide and sulfur dioxide.
机译:用于检测和识别有毒空气污染物的气体传感器类型之一是电催化气体传感器。电催化传感器以循环伏安模式工作,可检测各种气体。它们的响应呈Ⅰ-Ⅴ曲线形式,其中包含有关所测挥发性化合物的类型和浓度的信息。但是,需要进行其他分析才能有效识别目标气体。多元数据分析和模式识别方法被证明是用于此类应用的有用工具,但是需要对传感器响应处理的改进进行进一步研究。本文介绍了一种从电催化传感器响应中提取参数的方法。提取的特征可以在不降低识别四种挥发性空气污染物(即二氧化氮,氨,硫化氢和二氧化硫)的效率的情况下,显着减小数据量。

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