Combustible Gas Classification Modeling using Support Vector Machine and Pairing Plot Scheme

Combustible gases, such as CH and CO, directly or indirectly affect the human body. Thus, leakage detection of combustible gases is essential for various industrial sites and daily life. Many types of gas sensors are used to identify these combustible gases, but since gas sensors generally have low...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2019-11, Vol.19 (22), p.5018
Main Authors: Jang, Kyu-Won, Choi, Jong-Hyeok, Jeon, Ji-Hoon, Kim, Hyun-Seok
Format: Article
Language:English
Subjects:
Algorithms
Carbon monoxide
Classification
Communication
Datasets
Decoupling
decoupling algorithm
Experiments
Flammability
gas classification
Gas sensors
Gases
Leak detection
Machine learning
Methane
Microelectromechanical systems
pairing plot
Selectivity
semiconductor gas sensor
Sensors
support vector machine
Support vector machines
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Summary:Combustible gases, such as CH and CO, directly or indirectly affect the human body. Thus, leakage detection of combustible gases is essential for various industrial sites and daily life. Many types of gas sensors are used to identify these combustible gases, but since gas sensors generally have low selectivity among gases, coupling issues often arise which adversely affect gas detection accuracy. To solve this problem, we built a decoupling algorithm with different gas sensors using a machine learning algorithm. Commercially available semiconductor sensors were employed to detect CH and CO, and then support vector machine (SVM) applied as a supervised learning algorithm for gas classification. We also introduced a pairing plot scheme to more effectively classify gas type. The proposed model classified CH and CO gases 100% correctly at all levels above the minimum concentration the gas sensors could detect. Consequently, SVM with pairing plot is a memory efficient and promising method for more accurate gas classification.
ISSN:1424-8220
1424-8220
DOI:10.3390/s19225018