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

Carbon nanotube-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 paper presents an experimental determination of the single-value sensitivity of the sensor to hydrogen (H2), 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.