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Article

Odor Recognition of Thermal Decomposition Products of Electric Cables Using Odor Sensing Arrays

by
Yuanchang Liu
1,*,
Shintaro Furuno
1,
Sosuke Akagawa
1,
Rui Yatabe
1,
Takeshi Onodera
1,
Nobuyuki Fujiwara
2,
Hidekazu Takeda
2,
Seiichi Uchida
1 and
Kiyoshi Toko
3,4
1
Graduate School of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
2
Meidensha Corporation, ThinkPark Tower, 2-1-1 Osaki, Shinagawa-ku, Tokyo 141-6029, Japan
3
Research and Development Center for Five-Sense Devices, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
4
Institute for Advanced Study, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
*
Author to whom correspondence should be addressed.
Chemosensors 2021, 9(9), 261; https://doi.org/10.3390/chemosensors9090261
Submission received: 1 August 2021 / Revised: 29 August 2021 / Accepted: 7 September 2021 / Published: 10 September 2021
(This article belongs to the Special Issue Bioinspired Chemical Sensors and Micro-Nano Devices)
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Abstract

An odor sensing system with chemosensitive resistors was used to identify the gases generated from overheated cables to prevent fire. Three different electric cables for a distribution cabinet were used. The cables had an insulation layer made of polyvinyl chloride (PVC) or cross-linked polyethylene (XLPE). The heat resistance of the cables was tested by differential thermal and thermogravimetric analyses. The thermal decomposition products of the cables were investigated by gas chromatography-mass spectrometry (GC-MS). For the odor sensing system, two types of 16-channel array were used to detect the generated gases. One contains high-polarity GC stationary phase materials and the other contains GC stationary phase materials of high to low polarity. The system could distinguish among three cable samples at 270 °C with an accuracy of about 75% through both arrays trained with machine learning. Furthermore, the system could achieve a recall rate of 90% and a precision rate of 70% when the abnormal temperature was set above the cables’ allowable conductor temperature at 130 °C. The odor sensing system could effectively detect the abnormal heating of the cables before the occurrence of fire. Therefore, it is helpful for fire prediction and detection systems in factories and substations.
Keywords: GC materials; carbon black; odor sensor; artificial olfaction; chemical sensing; sensor array; decomposition of electric cable; safety devices; odor discrimination; machine learning GC materials; carbon black; odor sensor; artificial olfaction; chemical sensing; sensor array; decomposition of electric cable; safety devices; odor discrimination; machine learning

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MDPI and ACS Style

Liu, Y.; Furuno, S.; Akagawa, S.; Yatabe, R.; Onodera, T.; Fujiwara, N.; Takeda, H.; Uchida, S.; Toko, K. Odor Recognition of Thermal Decomposition Products of Electric Cables Using Odor Sensing Arrays. Chemosensors 2021, 9, 261. https://doi.org/10.3390/chemosensors9090261

AMA Style

Liu Y, Furuno S, Akagawa S, Yatabe R, Onodera T, Fujiwara N, Takeda H, Uchida S, Toko K. Odor Recognition of Thermal Decomposition Products of Electric Cables Using Odor Sensing Arrays. Chemosensors. 2021; 9(9):261. https://doi.org/10.3390/chemosensors9090261

Chicago/Turabian Style

Liu, Yuanchang, Shintaro Furuno, Sosuke Akagawa, Rui Yatabe, Takeshi Onodera, Nobuyuki Fujiwara, Hidekazu Takeda, Seiichi Uchida, and Kiyoshi Toko. 2021. "Odor Recognition of Thermal Decomposition Products of Electric Cables Using Odor Sensing Arrays" Chemosensors 9, no. 9: 261. https://doi.org/10.3390/chemosensors9090261

APA Style

Liu, Y., Furuno, S., Akagawa, S., Yatabe, R., Onodera, T., Fujiwara, N., Takeda, H., Uchida, S., & Toko, K. (2021). Odor Recognition of Thermal Decomposition Products of Electric Cables Using Odor Sensing Arrays. Chemosensors, 9(9), 261. https://doi.org/10.3390/chemosensors9090261

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