Combustible Gas Classification Modeling using Support Vector Machine and Pairing Plot Scheme
Combustible gases, such as CH<sub>4</sub> 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 sen...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/22/5018 |
| _version_ | 1828153157945917440 |
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| author | Kyu-Won Jang Jong-Hyeok Choi Ji-Hoon Jeon Hyun-Seok Kim |
| author_facet | Kyu-Won Jang Jong-Hyeok Choi Ji-Hoon Jeon Hyun-Seok Kim |
| author_sort | Kyu-Won Jang |
| collection | DOAJ |
| description | Combustible gases, such as CH<sub>4</sub> 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<sub>4</sub> 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<sub>4</sub> 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. |
| first_indexed | 2024-04-11T22:21:26Z |
| format | Article |
| id | doaj.art-df5a231029e1408a832349a760aaf2c2 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T22:21:26Z |
| publishDate | 2019-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-df5a231029e1408a832349a760aaf2c22022-12-22T04:00:07ZengMDPI AGSensors1424-82202019-11-011922501810.3390/s19225018s19225018Combustible Gas Classification Modeling using Support Vector Machine and Pairing Plot SchemeKyu-Won Jang0Jong-Hyeok Choi1Ji-Hoon Jeon2Hyun-Seok Kim3Division of Electronics and Electrical Engineering, Dongguk University-Seoul, Seoul 04620, KoreaDivision of Electronics and Electrical Engineering, Dongguk University-Seoul, Seoul 04620, KoreaDivision of Electronics and Electrical Engineering, Dongguk University-Seoul, Seoul 04620, KoreaDivision of Electronics and Electrical Engineering, Dongguk University-Seoul, Seoul 04620, KoreaCombustible gases, such as CH<sub>4</sub> 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<sub>4</sub> 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<sub>4</sub> 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.https://www.mdpi.com/1424-8220/19/22/5018semiconductor gas sensordecoupling algorithmgas classificationpairing plotsupport vector machine |
| spellingShingle | Kyu-Won Jang Jong-Hyeok Choi Ji-Hoon Jeon Hyun-Seok Kim Combustible Gas Classification Modeling using Support Vector Machine and Pairing Plot Scheme Sensors semiconductor gas sensor decoupling algorithm gas classification pairing plot support vector machine |
| title | Combustible Gas Classification Modeling using Support Vector Machine and Pairing Plot Scheme |
| title_full | Combustible Gas Classification Modeling using Support Vector Machine and Pairing Plot Scheme |
| title_fullStr | Combustible Gas Classification Modeling using Support Vector Machine and Pairing Plot Scheme |
| title_full_unstemmed | Combustible Gas Classification Modeling using Support Vector Machine and Pairing Plot Scheme |
| title_short | Combustible Gas Classification Modeling using Support Vector Machine and Pairing Plot Scheme |
| title_sort | combustible gas classification modeling using support vector machine and pairing plot scheme |
| topic | semiconductor gas sensor decoupling algorithm gas classification pairing plot support vector machine |
| url | https://www.mdpi.com/1424-8220/19/22/5018 |
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