| The corn deep-processing is water-based and needs to consume plenty of water resources. During the process, meanwhile, the increased cyclic utilization of process water greatly interferes with the stable operation of original technological production, thus leading to a greater possibility of production accidents. Generally the occurrence of production accidents will increase the pollutant concentration of production wastewater and result in excessive discharge of wastewater, and consequently make it more difficult to abate wastewater pollution and impose a threat to enterprise wastewater treatment and water pollution. Therefore, to predict accidents during the production and operation of corn deep-processing enterprises, monitor on a real-time basis the enterprises production indexes, keep stable the enterprises’ production and operation, reduce wastewater and water pollutants from the source, and bring down the emission of water pollutants is of important practical significance for protecting the environment and preventing industrial water pollution.By taking the technological production of a corn deep-processing enterprise as research object and utilizing the geographic information system(GIS) technology, wireless sensor network technology, database technology and network technology, this subject research delves into the GIS-based forewarning system of corn deep-processing enterprises and develops a production accident forewarning system that integrates the automatic monitoring, real-time transmission, storage and management of production data, comprehensive analysis and prediction, and network publishing. The author firstly introduces the background, significance, the relevant research status at home and abroad of this subject research, and explains the theoretical bases of such key technologies as GIS, modern sensor network, and database. On that basis, the author secondly analyzes the system according to the enterprise’s demand for forewarning, and utilizes GIS’s powerful graphic and attribute data management to draw the process flow diagram, collect and input the data of technological production, and establish a visual, advanced, accurate GIS-based information management frame system for the technological process of production. Thirdly, wireless sensor technology and computer technology are utilized to develop and design the data acquisition module and to select forewarning and monitoring indexes. The production data is also collected on site, and the database is dynamically monitored by SQL Server and connected to the GIS forewarning system to realize real-time update of production data. Fourthly, the technological production forewarning mechanism is established, the accident emergency plan formulated, and a forewarning model built. Finally, the forewarning system is shared and published on the Web via the well-developed Arc GIS Server, and the application function of WebGIS is also developed to make sure users can access to the forewarning system through enterprise intranet or the Internet.The system implements the forewarning of production accidents for corn deep-processing enterprises.By monitoring and predicting production indexes, it realizes the dynamic monitoring and forewarning management of enterprise production, stabilizes production and operation, and prevents the excessive emission of production wastewater and industrial water pollution caused by production accidents. In the meanwhile, the introduction of GIS and wireless sensor network to the system offers a platform to visually present production graphs and data, saves the cost of data communication, realizes the sharing of system resources, and makes the design and implementation of forewarning system innovative and economical to some extent. |
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