测试技术学报2025，Vol.39Issue(1)：88-95,8.DOI:10.62756/csjs.1671-7449.2025013
基于快速温度调制的气体传感器选择性提高方法
Improving Selectivity of Gas Sensor Based on Rapid Temperature Modulation
摘要
Abstract
To address the poor selectivity and cross-sensitivity of metal-oxide-semiconductor sensors,a fast temperature modulation method was used with an individual MEMS gas sensor to construct a virtual sensor array,which has lower power consumption and cost.First,the response signals to different gases were obtained under pulse temperature modulation and the modulation parameters were optimized.Then,a Support Vector Machine was employed to identify the types of different gases,and Support Vector Regression,Random Forest Regression,and Back-propagation neural network algorithms were employed to estimate the concentration of each gas.The results show that all four gases,H2,H2S,NH3 and C2H5OH,were correctly classified with concentration prediction errors of 19.5×10-6,3.7×10-6,0.2×10-6 and 19×10-6,respectively.This method improves the selectivity of individual gas sensors while reducing power consumption,providing ideas and solutions for on-site detection such as environmental monitoring and industrial production.关键词
气体传感器/选择性/温度调制/模式识别Key words
gas sensor/selectivity/temperature modulation/pattern recognition分类
信息技术与安全科学引用本文复制引用
林凯滨,林建华,贾建,高晓光,何秀丽..基于快速温度调制的气体传感器选择性提高方法[J].测试技术学报,2025,39(1):88-95,8.基金项目
国家重点研发计划资助项目(2021YFB3201300) （2021YFB3201300）
