Research On Identification And Monitoring Of The Industrial Exhaust Gas Pollution Sources

At present, industrial exhaust gas pollution is becoming more and more serious, reducing the quality of human life. Therefore, identification and monitoring of the industrial exhaust gas pollution source has become a worldwide focus. The government has set strict rules on industrial emissions standards:Emissions should meet the standard, and exceeding emissions is illegal. But there are still some enterprises that ignore the laws and discharge pollutants secretly or exceedingly. In order to monitor pollution emissions effectively, we must identify and monitor the source of industrial exhaust gas pollution. Therefore, designing a system that can distinguish the source of exhaust gas pollution automatically and monitor the source effectively is of vital significance.To solve this problem, a method that can identify the direction of air pollution source automatically and rapidly was proposed. A multi-sensor system based on Bayesian mathematical model was designed, which can identify the direction of air pollution source. The detection system consisted of four gas sensors, all of which were fixed evenly on the same circle every 90 degrees. The system can identify 16 directions and the resolution of the identification is 22.5 degrees. Firstly, eight standard directions were calibrated, and the prior probability of each direction should be confirmed. Then the posterior probability of each direction was calculated by Bayesian mathematical model according to the prior probability of each direction and real-time sample values of air pollution source detected by sensors. And then the direction of air pollution source was decided based on posterior probabilities.The analytical results and the real-time sample values detected by sensors could be transmitted to the terminal monitoring system by wireless video server through the local area network, realizing remote monitoring. In addition, reviewing and analysis of the historical data is available.The experimental data indicate that the method researched in this paper to identify and monitor the industrial exhaust gas pollution sources based on Bayesian mathematical model and remote monitoring is feasible and valid.