The Design And Implementation Of Digital Chemical Factory Warning System

With the rapid development of the chemical industry, the produces and storage of chemicals has been greatly improved in recent years. Meanwhile, the environmental pollution accidents caused by the transportation and storage of the poisonous and hazardous chemicals are rising day by day, which is so harmful to human lives and the environment. And now it has become a common concern around the world. Therefore, using mathematical models to predict the influence of the atmospheric pollutants diffusion and warn it, through the reasonable management of monitoring data, at the same time, establishing the emergency rescue information system to research the matter of rescue resources and the evacuation of paths, which will be essential to chemical process. And the research of chemical warning system has become an inevitable question of modern production.Firstly, the paper select Gaussian model as the research model, by a comparative analysis on different diffusion models, and analyze the parameters of the Gaussian model selection and the limitations of the model application. Then, concerning the obvious calculation error questions, the research has introduced the terrain factor calculation model and improved the source Gaussian model to make it more adaptable. At last, the research has analyzed the geographical coordinate system and Gaussian coordinates transform method are analyzed in detail.The paper has designed geographic information database and basic information database based on ArcGIS Engine, C# programming environment, and using SQL Server 2008 as database management software and established the digital factory warning system eventually. This system contains several common basic functions, for instance inquiring of surrounding ground features, monitoring data management, emergency supplies, and rescue path analysis function. Visually displaying the influence of gas leakage accident area, and providing basis to the emergency warning policy for the chemical accidents, by the combination of GIS function with Gaussian model.