College of Communication Engineering, Chongqing University, 174 ShaZheng Street, ShaPingBa District, Chongqing, 400044, China.
College of Communication Engineering, Chongqing University, 174 ShaZheng Street, ShaPingBa District, Chongqing, 400044, China.
Anal Chim Acta. 2017 Sep 15;986:145-152. doi: 10.1016/j.aca.2017.07.028. Epub 2017 Jul 15.
A sensor array with 30 gas sensors is used in the electronic nose (e-nose) for bacteria detection in wound infection. However, the interference is an urgent problem in e-nose, since it would impact on the detection of target due to the cross-sensitivity of gas sensors, especially the background interference caused by carrier gas. The related methods to suppress the background interference are independent component analysis and orthogonal signal correction algorithm which are unreasonable, because it is difficult to obtain the so-called reference vector in complex real-world scenario. Consider that the sampling process of pump suction is divided into three parts: baseline collecting, sample collecting and system purging. In the case of stabilized carrier gas, the information in baseline can be fully used to suppress the interference in sampling stage. Thus a novel and effective correlated information removing based interference suppression (CIRIS) method is proposed. Specifically, the principle of this method is to suppress the interference of the sampling stage by removing the information correlated with baseline samples. Experimental results show that the proposed method (CIRIS with principal component analysis used to calculate the projection matrix) is significantly effective for interference suppression in e-nose.
电子鼻（e-nose）中使用带有 30 个气体传感器的传感器阵列来检测伤口感染中的细菌。然而，由于气体传感器的交叉敏感性，尤其是载气引起的背景干扰，干扰是 e-nose 中的一个紧迫问题。抑制背景干扰的相关方法是独立成分分析和正交信号校正算法，这是不合理的，因为在复杂的实际场景中很难获得所谓的参考向量。考虑到泵吸采样过程分为三个部分：基线采集、样品采集和系统吹扫。在稳定载气的情况下，可以充分利用基线中的信息来抑制采样阶段的干扰。因此，提出了一种新颖有效的基于相关信息消除的干扰抑制（CIRIS）方法。具体来说，该方法的原理是通过去除与基线样本相关的信息来抑制采样阶段的干扰。实验结果表明，所提出的方法（基于主成分分析计算投影矩阵的 CIRIS）对于电子鼻中的干扰抑制非常有效。
