Differential Electronic Nose in On-Line Dynamic Measurements

Abstract The paper presents application of differential electronic nose in the dynamic (on-line) volatile measurement. First we compare the classical nose employing only one sensor array and its extension in the differential form containing two sensor arrays working in differential mode. We show that differential nose performs better at changing environmental conditions, especially the temperature, and well performs in the dynamic mode of operation. We show its application in recognition of different brands of tobacco

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Sensor arrays: an inspired idea or an objective measurement of environmental odours?

Water Science & Technology ◽

10.2166/wst.2001.0507 ◽

2001 ◽

Vol 44 (9) ◽

pp. 53-58 ◽

Cited By ~ 13

Author(s):

R.M. Stuetz ◽

J. Nicolas

Keyword(s):

Sensor Array ◽

Sensory System ◽

Sensor Arrays ◽

Objective Measurement ◽

Chemical Compositions ◽

Response Patterns ◽

Human Response ◽

Control And Prevention ◽

On Line ◽

The Right

The measure of annoyance odours from sewage tratment, landfill and agricultural practise has become highly significant in the control and prevention of dorous emissions from existing facilities and its crucial for new planning applications. Current methods (such as GC-MS analysis, H2S and NH3 measurements) provide an accurate description of chemical compositions or act as surrogates for odour strength, but tell us very little about the perceived effect, whereas olfactometry gives the right human response but is very subjective and expensive. The use of non-specific sensor arrays may offer an objective and on-line instrument for assessing olfactive annoyance. Results have shown that sensor array systems can discriminate between different odour sources (wastewater, livestock and landfill). The response patterns from these sources can be significantly different and that the intensity of sensor responses is proportional to the concentration of the volatiles. The correlation of the sensors responses against odour strengths have also shown that reasonable fits can be obtained for a range of odour concentrations (100-800,000 ou/m3). However, the influence of environmental fluctuations (humidity and temperature) on sensor baselines still remains an obstacle, as well as the need for periodic calibration of the sensory system and the choice of a suitable gas for different environmental odours.

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Chemical Sensor Array Modeling: Application to Resistive Based Chemo Sensors

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.605.15 ◽

2014 ◽

Vol 605 ◽

pp. 15-18

Author(s):

Abdelaziz Abbas ◽

Ahcene Bouabdallah

Keyword(s):

Mathematical Models ◽

Differential Form ◽

Sensor Array ◽

Chemical Sensor ◽

Sensor Arrays ◽

Gas Mixture ◽

State Equations ◽

Dynamical Equilibrium ◽

Chemical Sensor Array ◽

Intensive Quantities

The aim of paper is to develop analytical mathematical models that describe the thermo dynamical equilibrium of resistive chemical sensor arrays /mixture of vapors multi-system. By using the Gibbs Duhem formalism, state equations in differential form, that the variations of intensive quantities (e.g. sensors partial sensitivity) as function of the gas mixture components concentrations and sensor array parameters describe, have been developed. Moreover, the responses of the sensor arrays as function of gas mixture components concentrations were modeled.

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

Sensor Review ◽

10.1108/sr-02-2013-630 ◽

2014 ◽

Vol 34 (3) ◽

pp. 304-311 ◽

Cited By ~ 14

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.

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Study on Sensor Array Optimization of Medical Electronic Nose for Wound Infection Detection

IEEE Transactions on Circuits & Systems II Express Briefs ◽

10.1109/tcsii.2021.3112597 ◽

2021 ◽

pp. 1-1

Author(s):

Junhui Qian ◽

Mengchen Lu ◽

Fengchun Tian ◽

Ran Liu

Keyword(s):

Wound Infection ◽

Electronic Nose ◽

Sensor Array ◽

Infection Detection ◽

Medical Electronic ◽

Array Optimization

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

Journal of Nanoelectronics and Optoelectronics ◽

10.1166/jno.2021.2955 ◽

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.

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Applications of Electronic-Nose Technologies for Noninvasive Early Detection of Plant, Animal and Human Diseases

Chemosensors ◽

10.3390/chemosensors6040045 ◽

2018 ◽

Vol 6 (4) ◽

pp. 45 ◽

Cited By ~ 13

Author(s):

Alphus Dan Wilson

Keyword(s):

Electronic Nose ◽

Gas Sensing ◽

Sensor Arrays ◽

Human Diseases ◽

Detection Methods ◽

Research Progress ◽

Disease Detection ◽

New Information ◽

Disease Diagnostics ◽

Diagnostic Applications

The development of electronic-nose (e-nose) technologies for disease diagnostics was initiated in the biomedical field for detection of biotic (microbial) causes of human diseases during the mid-1980s. The use of e-nose devices for disease-diagnostic applications subsequently was extended to plant and animal hosts through the invention of new gas-sensing instrument types and disease-detection methods with sensor arrays developed and adapted for additional host types and chemical classes of volatile organic compounds (VOCs) closely associated with individual diseases. Considerable progress in animal disease detection using e-noses in combination with metabolomics has been accomplished in the field of veterinary medicine with new important discoveries of biomarker metabolites and aroma profiles for major infectious diseases of livestock, wildlife, and fish from both terrestrial and aquaculture pathology research. Progress in the discovery of new e-nose technologies developed for biomedical applications has exploded with new information and methods for diagnostic sampling and disease detection, identification of key chemical disease biomarkers, improvements in sensor designs, algorithms for discriminant analysis, and greater, more widespread testing of efficacy in clinical trials. This review summarizes progressive advancements in utilizing these specialized gas-sensing devices for numerous diagnostic applications involving noninvasive early detections of plant, animal, and human diseases.

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Fundamental Sensor Development in Electrical Resistance Tomography

Jurnal Teknologi ◽

10.11113/jt.v73.4431 ◽

2015 ◽

Vol 73 (6) ◽

Cited By ~ 1

Author(s):

Ling En Hong ◽

Ruzairi Hj. Abdul Rahim ◽

Anita Ahmad ◽

Mohd Amri Md. Yunus ◽

Khairul Hamimah Aba ◽

...

Keyword(s):

Image Reconstruction ◽

Data Acquisition ◽

Electrical Resistance ◽

Sensor Array ◽

Sensor Arrays ◽

Region Of Interest ◽

Display System ◽

Electrical Resistance Tomography ◽

Fundamental Understanding ◽

Collection Strategies

This paper will provide a fundamental understanding of one of the most commonly used tomography, Electrical Resistance Tomography (ERT). Unlike the other tomography systems, ERT displayed conductivity distribution in the Region of Interest (ROI) and commonly associated to Sensitivity Theorem in their image reconstruction. The fundamental construction of ERT includes a sensor array spaced equally around the imaged object periphery, a Data Acquisition (DAQ), image reconstruction and display system. Four ERT data collection strategies that will be discussed are Adjacent Strategy, Opposite Strategy, Diagonal Strategy and Conducting Boundary Strategy. We will also explain briefly on some of the possible Data Acquisition System (DAQ), forward and inverse problems, different arrangements for conducting and non-conducting pipes and factors that influence sensor arrays selections.

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