Dynamic Measurement and Recognition Methods of SnO<sub>2</sub> Sensor to VOCs Under Zigzag-Rectangular Wave Temperature Modulation
Fanli Meng, Hanyang Ji, Zhenyu Yuan, Yaru Chen, Hua Zhang, Wenbo Qin, Hongliang Gao
Abstract
Semiconductor gas sensors have been widely applied to Volatile Organic Compounds (VOCs) detection. However, the poor selectivity in the actual complex gas environment has become a bottleneck to restrict the development of semiconductor gas sensors. In order to solve this problem, SnO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> gas sensor is prepared and temperature modulation measurement is carried out. In this paper, the method of zigzag-rectangular wave temperature modulation is first proposed, which improved the selectivity of the sensor and significantly increased the characteristic peak. Support vector machine (SVM) is used for pattern recognition, which proved the superior of the SVM in small sample size. The results demonstrate that the combination of zigzag-rectangular wave temperature modulation and SVM pattern recognition method can effectively improve the selectivity of the gas sensor.