Thermopile sensor array for an electronic nose integrated non-selective NDIR gas detection system

2005 ◽  
Author(s):  
R. Rubio ◽  
J. Santander ◽  
N. Sabate ◽  
L. Fonseca ◽  
I. Garcia ◽  
...  
Keyword(s):  
Electronic Nose ◽  
Sensor Array ◽  
Detection System ◽  
Gas Detection ◽  
Thermopile Sensor

A portable embedded explosion gas detection and identification device based on intelligent electronic nose system

Sensor Review ◽  
2016 ◽  
Vol 36 (1) ◽  
pp. 57-63 ◽  
Author(s):  
Gu Gong ◽  
Hua Zhu
Keyword(s):  
Electronic Nose ◽  
Chemical Sensors ◽  
Olfactory System ◽  
Sensor Array ◽  
Detection System ◽  
Gas Detection ◽  
Content Type ◽  
Detection And Identification ◽  
Before And After ◽  
Promising Perspective

Purpose – The purpose of this study satisfied the need for rapid, sensitive and highly portable identification of an explosion gas. In our study, a battery-operated, low-cost and portable gas detection system consisting of a cataluminescence-based sensor array was developed for the detection and identification of explosion gas. This device shows how the discriminatory capacity of sensor arrays utilizing pattern recognition operate in environments. Design/methodology/approach – A total of 25 sensor units, including common metal oxides and decorated materials, have been carefully selected as sensing elements of 5 × 5 sensor array. Dynamic and static analysis methods were utilized to characterize the performance of the explosion gas detection system to five kinds of explosion gases. The device collects images of chemical sensors before and after exposing to the target gas and then processes those images to extract the unique characteristic for each gas. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used to analyze the image patterns. Findings – Our study demonstrated that the portable gas detection device shows promising perspective for the recognition and discrimination of explosion gas. It can be used for the olfactory system of robot made by integrating the electronic nose and computer together. Originality/value – The device collects images of chemical sensors before and after exposing to the target gas and then processes those images to extract the unique characteristic for each gas. HCA and (PCA were used to analyze the image patterns. Our study demonstrated that the portable gas detection device shows promising perspective for the recognition and discrimination of explosion gas. It can be used for olfactory system of robot made by integrating the electronic nose and computer together.

Design of a Gas Detection System Based on BP Neural Network

2011 ◽  
Vol 55-57 ◽  
pp. 1819-1823
Author(s):  
Yin Long Wang ◽  
Ke Cheng Lin ◽  
Xi Wu Wang ◽  
Zhi Guang Geng ◽  
Qi Gen Zhong
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Gas Sensor ◽  
Sensor Array ◽  
Detection System ◽  
Gas Detection ◽  
Gas Sensor Array ◽  
Array Technology ◽  
Artificial Neural ◽  
Different Gases

On the basis of the brief overview of principles of the gas detection system, this paper has analyzed the characteristics, structure and identification theory to explain the method of gas detection based on an artificial neural network. And it has analyzed and researched gas detection system based on neural network and thus solved the problems such as cross-sensitiveness in present gas sensor. The results show that the gas sensor array "cross-sensitive" issue can be effectively solved through the combination of the pattern recognition of artificial neural network and the gas sensor array technology, which accordingly realizes qualitative identification for different gases and has broad application prospects.

A novel sensor array and classifier optimization method of electronic nose based on enhanced quantum-behaved particle swarm optimization

Sensor Review ◽  
2014 ◽  
Vol 34 (3) ◽  
pp. 304-311 ◽  
Author(s):  
Pengfei Jia ◽  
Fengchun Tian ◽  
Shu Fan ◽  
Qinghua He ◽  
Jingwei Feng ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Wound Infection ◽  
Electronic Nose ◽  
Classification Accuracy ◽  
Sensor Array ◽  
Particle Swarm ◽  
Optimization Method ◽  
Support Vector ◽  
Swarm Optimization ◽  
Content Type

Purpose – The purpose of the paper is to propose a new optimization algorithm to realize a synchronous optimization of sensor array and classifier, to improve the performance of E-nose in the detection of wound infection. When an electronic nose (E-nose) is used to detect the wound infection, sensor array’s optimization and parameters’ setting of classifier have a strong impact on the classification accuracy. Design/methodology/approach – An enhanced quantum-behaved particle swarm optimization based on genetic algorithm, genetic quantum-behaved particle swarm optimization (G-QPSO), is proposed to realize a synchronous optimization of sensor array and classifier. The importance-factor (I-F) method is used to weight the sensors of E-nose by its degree of importance in classification. Both radical basis function network and support vector machine are used for classification. Findings – The classification accuracy of E-nose is the highest when the weighting coefficients of the I-F method and classifier’s parameters are optimized by G-QPSO. All results make it clear that the proposed method is an ideal optimization method of E-nose in the detection of wound infection. Research limitations/implications – To make the proposed optimization method more effective, the key point of further research is to enhance the classifier of E-nose. Practical implications – In this paper, E-nose is used to distinguish the class of wound infection; meanwhile, G-QPSO is used to realize a synchronous optimization of sensor array and classifier of E-nose. These are all important for E-nose to realize its clinical application in wound monitoring. Originality/value – The innovative concept improves the performance of E-nose in wound monitoring and paves the way for the clinical detection of E-nose.

Domestic gas detection system using two SnO2 integrated sensors

1994 ◽  
Vol 19 (1-3) ◽  
pp. 658-660 ◽  
Author(s):  
V. Demarne ◽  
B. Romanowicz ◽  
A. Grisel ◽  
J. Fournier
Keyword(s):  
Detection System ◽  
Gas Detection ◽  
Integrated Sensors

Nano Sensor Using One Dimensional Porous Indium Oxide and Pattern Recognition Method of Its Electronic Information

2021 ◽  
Vol 16 (2) ◽  
pp. 255-263
Author(s):  
Qinghong Wu ◽  
Wanying Zhang
Keyword(s):  
Pattern Recognition ◽  
Indium Oxide ◽  
Electronic Nose ◽  
Sensor Array ◽  
Dimensional Space ◽  
Ordinary Least Squares ◽  
Acquisition Time ◽  
Pattern Recognition Method ◽  
Recognition Method ◽  
Linear Discriminant

Due to its high sensitivity, low price and fast response speed, gas sensors based on metal oxide nanomate-rials have attracted many researchers to modify and explore the materials. First, pure indium oxide (In2O3) nanotubes (NTs)/porous NTs (PNTs) and Ho doped In2O3 NTs/PNTs are prepared by electrospinning and calcination. Then, based on the prepared nanomaterials, the 6-channel sensor array is obtained and used in the electronic nose sensing system for wine product identification. The system obtains the frequency signals of different liquor products by means of 6-channel sensor array, analyzes the extracted electronic signal characteristic information by means of ordinary least squares, and introduces the pattern recognition method of moving average and linear discriminant to identify liquor products. In the experiment, compared with pure In2O3 NTs sensor, pure In2O3 PNTs sensor has higher sensitivity to 100 ppm ethanol gas, and the sensitivity is further improved after mixing Ho. Among them, 6 mol% Ho + In2O3 PNTs have the highest sensitivity and the shortest response time; based on the electronic nose system composed of prepared nanomaterial sensor array, frequency signals of different Wu Liang Ye wines are collected. With the extension of acquisition time, the corresponding frequency first decreases and then becomes stable; the extracted liquor characteristic signal is projected into two-dimensional space and three-dimensional space. The results show that the pattern recognition system based on this method can extract the characteristic signals of liquor products and distinguish them.

scholarly journals Sensor array optimization techniques for exhaled breath analysis to discriminate diabetics using an electronic nose

ETRI Journal ◽  
2018 ◽  
Vol 40 (6) ◽  
pp. 802-812 ◽  
Author(s):  
Jin-Young Jeon ◽  
Jang-Sik Choi ◽  
Joon-Boo Yu ◽  
Hae-Ryong Lee ◽  
Byoung Kuk Jang ◽  
...  
Keyword(s):  
Electronic Nose ◽  
Sensor Array ◽  
Breath Analysis ◽  
Optimization Techniques ◽  
Exhaled Breath ◽  
Exhaled Breath Analysis ◽  
Array Optimization
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