scholarly journals k-NN and k-NN-ANN Combined Classifier to Assess MOX Gas Sensors Performances Affected by Drift Caused by Early Life Aging

Chemosensors ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 6
Author(s):  
Marco Abbatangelo ◽  
Estefanía Núñez-Carmona ◽  
Veronica Sberveglieri ◽  
Elisabetta Comini ◽  
Giorgio Sberveglieri
Keyword(s):  
Gas Sensors ◽  
Chemical Sensors ◽  
Early Life ◽  
Aging Process ◽  
Nearest Neighbors ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Alcohol Content ◽  
K Nearest Neighbors ◽  
Combined Classifier

The drift of metal oxide semiconductor (MOX) chemical sensors is one of the most important topics in this field. The work aims to test the performance of MOX gas sensors over the aging process. Firstly, sensors were tested with ethanol to understand their behavior and response changes. In parallel, beers with different alcoholic content were analyzed to assess what happened in a real application scenario. With ethanol analysis, it was possible to quantify drift of the baseline of the sensors and changes that could affect their responses over time (from day 1 to day 51). Conversely, the beer dataset has been exploited to evaluate how two different classifiers perform the classification task based on the alcohol content of the samples. A hybrid k-nearest neighbors artificial neural network (k-NN-ANN) approach and “standard” k-NN were used to evaluate to distinguish among the samples when the measures were affected by drift. To achieve this goal, data acquired from day one to day six were used as training to predict data collected up to day 51. Overall, performances of the two methods were similar, even if the best result in terms of accuracy is reached by k-NN-ANN (96.51%).

scholarly journals A Prototype to Detect the Alcohol Content of Beers Based on an Electronic Nose

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2646 ◽  
Author(s):  
Henike Guilherme Jordan Voss ◽  
José Jair Alves Mendes Júnior ◽  
Murilo Eduardo Farinelli ◽  
Sergio Luiz Stevan
Keyword(s):  
Metal Oxide ◽  
Electronic Nose ◽  
Gas Sensors ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Alcohol Content ◽  
Electronic Noses

Due to the emergence of new microbreweries in the Brazilian market, there is a need to construct equipment to quickly and accurately identify the alcohol content in beverages, together with a reduced marketing cost. Towards this purpose, the electronic noses prove to be the most suitable equipment for this situation. In this work, a prototype was developed to detect the concentration of ethanol in a high spectrum of beers presents in the market. It was used cheap and easy-to-acquire 13 gas sensors made with a metal oxide semiconductor (MOS). Samples with 15 predetermined alcohol contents were used for the training and construction of the models. For validation, seven different commercial beverages were used. The correlation (R2) of 0.888 for the MLR (RMSE = 0.45) and the error of 5.47% for the ELM (RMSE = 0.33) demonstrate that the equipment can be an effective tool for detecting the levels of alcohol contained in beverages.

scholarly journals Field Study of Metal Oxide Semiconductor Gas Sensors in Temperature Cycled Operation for Selective VOC Monitoring in Indoor Air

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 647
Author(s):  
Tobias Baur ◽  
Johannes Amann ◽  
Caroline Schultealbert ◽  
Andreas Schütze
Keyword(s):  
Air Quality ◽  
Metal Oxide ◽  
Gas Sensor ◽  
Gas Sensors ◽  
Indoor Air ◽  
Ambient Air ◽  
Quantitative Agreement ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
High Temporal Resolution

More and more metal oxide semiconductor (MOS) gas sensors with digital interfaces are entering the market for indoor air quality (IAQ) monitoring. These sensors are intended to measure volatile organic compounds (VOCs) in indoor air, an important air quality factor. However, their standard operating mode often does not make full use of their true capabilities. More sophisticated operation modes, extensive calibration and advanced data evaluation can significantly improve VOC measurements and, furthermore, achieve selective measurements of single gases or at least types of VOCs. This study provides an overview of the potential and limits of MOS gas sensors for IAQ monitoring using temperature cycled operation (TCO), calibration with randomized exposure and data-based models trained with advanced machine learning. After lab calibration, a commercial digital gas sensor with four different gas-sensitive layers was tested in the field over several weeks. In addition to monitoring normal ambient air, release tests were performed with compounds that were included in the lab calibration, but also with additional VOCs. The tests were accompanied by different analytical systems (GC-MS with Tenax sampling, mobile GC-PID and GC-RCP). The results show quantitative agreement between analytical systems and the MOS gas sensor system. The study shows that MOS sensors are highly suitable for determining the overall VOC concentrations with high temporal resolution and, with some restrictions, also for selective measurements of individual components.

scholarly journals Synthesis of Metal Oxide Semiconductor Nanostructures for Gas Sensors

Gas Sensors ◽  
2020 ◽  
Author(s):  
Nazar Abbas Shah ◽  
Majeed Gul ◽  
Murrawat Abbas ◽  
Muhammad Amin
Keyword(s):  
Metal Oxide ◽  
Gas Sensors ◽  
Semiconductor Nanostructures ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor

scholarly journals Electronic Nose Technologies in Monitoring Black Tea Manufacturing Process

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Tharaga Sharmilan ◽  
Iresha Premarathne ◽  
Indika Wanniarachchi ◽  
Sandya Kumari ◽  
Dakshika Wanniarachchi
Keyword(s):  
Neural Network ◽  
Electronic Nose ◽  
Gas Sensors ◽  
Black Tea ◽  
Quality Parameters ◽  
Polyphenolic Compounds ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Optimum Level ◽  
Fermentation Stage

“Tea” is a beverage which has a unique taste and aroma. The conventional method of tea manufacturing involves several stages. These are plucking, withering, rolling, fermentation, and finally firing. The quality parameters of tea (color, taste, and aroma) are developed during the fermentation stage where polyphenolic compounds are oxidized when exposed to air. Thus, controlling the fermentation stage will result in more consistent production of quality tea. The level of fermentation is often detected by humans as “first” and “second” noses as two distinct smell peaks appear during fermentation. The detection of the “second” aroma peak at the optimum fermentation is less consistent when decided by humans. Thus, an electronic nose is introduced to find the optimum level of fermentation detecting the variation in the aroma level. In this review, it is found that the systems developed are capable of detecting variation of the aroma level using an array of metal oxide semiconductor (MOS) gas sensors using different statistical and neural network techniques (SVD, 2-NM, MDM, PCA, SVM, RBF, SOM, PNN, and Recurrent Elman) successfully.

Detection of triacetone triperoxide using temperature cycled metal-oxide semiconductor gas sensors

2015 ◽  
Vol 212 (6) ◽  
pp. 1289-1298 ◽  
Author(s):  
Johannes Warmer ◽  
Patrick Wagner ◽  
Michael J. Schöning ◽  
Peter Kaul
Keyword(s):  
Metal Oxide ◽  
Gas Sensors ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Triacetone Triperoxide ◽  
Semiconductor Gas Sensors
Sign in / Sign up

Export Citation Format

Share Document