The WOA-LSSVM Temperature Compensation Technology for Carbon Nanotube-Based Ionizing Gas Sensor

被引：0

作者：

Cheng, Zhenzhen ^{[1
]}

He, Guofeng ^{[1
]}

Liang, Chengwu ^{[1
]}

Dong, Yanfei ^{[1
]}

He, Wei ^{[1
]}

Hou, Ning ^{[1
]}

Guo, Yu ^{[1
]}

Guo, Wenkai ^{[1
]}

Zhang, Ruixue ^{[1
]}

Jiang, Canwei ^{[1
]}

机构：

[1] Henan Univ Urban Construct, Sch Elect & Control Engn, Pingdingshan 467041, Peoples R China

来源：

IEEE SENSORS JOURNAL | 2024年 / 24卷 / 21期

基金：

中国国家自然科学基金;

关键词：

Carbon nanotube (CNT); ionizing gas sensor; least-squares support vector machine (LSSVM); temperature compensation; whale optimization algorithm (WOA); HUMIDITY; MODEL;

D O I：

10.1109/JSEN.2024.3459940

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Carbon nanotube (CNT)-based ionizing gas sensors are susceptible to fluctuations in gas detection results due to variations in temperature, necessitating temperature compensation to align with real-world application standards. This article presents an experimental determination of the single-value sensitivity of the sensor to hydrogen (H-2), where the collecting current of the sensor was observed to decrease with rising hydrogen concentration and temperature. We introduce a novel temperature compensation model based on the least-squares support vector machine optimized by the whale optimization algorithm (WOA-LSSVM), which executes temperature compensation concurrently with hydrogen concentration detection. Post-implementation of temperature compensation, there has been a significant reduction in the temperature influence coefficient of the sensor by three orders of magnitude, resulting in a substantial enhancement in the sensor's detection performance.

引用

页码：35212 / 35220

页数：9

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