Features extraction from the electrocatalytic gas sensor responses

P. Kalinowski, Ł. Woźniak, M. Stachowiak, G. Jasinski, P. Jasiński
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Abstract

One of the types of gas sensors used for detection and identification of toxic-air pollutant is an electro-catalytic gas sensor. The electro-catalytic 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 electro-catalytic 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.
从电催化气体传感器响应中提取特征
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。电催化传感器在循环伏安模式下工作,可以检测各种气体。它们的响应以I-V曲线的形式呈现,其中包含有关所测挥发性化合物的类型和浓度的信息。然而,需要额外的分析来提供对目标气体的有效识别。多元数据分析和模式识别方法已被证明是此类应用的有用工具,但需要进一步研究传感器响应处理的改进。本文介绍了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影响识别四种挥发性空气污染物(二氧化氮、氨、硫化氢和二氧化硫)的效率的情况下显著降低数据维数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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