Research on temperature and humidity compensation method of vehicle gas sensor based on SCA-PSO support vector regression - Lv Yingming; Yuan Wenping (Dianzi Jishu Yingyong)
Nitrogen oxides and particulate matter are the two main pollutants emitted by diesel locomotive exhaust. It is an effective measure to control urban air pollution to monitor the exhaust emission of diesel locomotives by using the vehicle exhaust gas detection device. For a nitrogen oxide gas sensor, based on its detection principle, temperature and humidity will have a greater impact on the chemical reaction in the detection process, so a corresponding temperature and humidity compensation method is required to improve the measurement accuracy of the sensor. In this paper, a vehicle-mounted vehicle exhaust gas detection device is designed and a sensor temperature and humidity compensation method based on Support Vector Regression (SVR), Sine Cosine Algorithm(SCA) and Particle Swarm Optimization (PSO) is proposed. The concentration of nitrogen oxide gas and particulate matter, and the compensation model is used to compensate the temperature and humidity of the sensor detection value. After testing data training and validation, the compensation model can effectively reduce errors caused by temperature and humidity, and can meet engineering requirements.