Design And Implementation Of Jilin Petrochemical Sewage Supervision System Based On Big Data

Petrochemical enterprises will produce a large number of waste water,and the treatment of these wastewater is a complex industrial process,accompanied by a variety of characteristics such as diversity,non-linearity,variability and contingency.Previous methods of sewage treatment often used manual experience laboratory monitoring,treatment time delay,decentralized treatment process,but also to ensure the effectiveness of sewage treatment,so a large number of human material and resources to be wasted.With the development of artificial intelligence technology,many researchers believe that real-time sewage data can be mastered timely and effectively by intelligent auxiliary measurement method to ensure the stable and long-term operation of sewage treatment system.In recent years,researchers in the field of intelligence have published many articles and research results on the intellectualization of Sewage Monitoring and treatment,and the application of intellectualized analysis-assisted control of integrated sewage management system is called expert system.At the same time,the emergence of today's popular artificial neural network,data mining and large data technology can also be adapted.The sewage monitoring and prediction analysis is applied to the wastewater treatment plant.After comprehensive investigation and research in this field at home and abroad,aiming at the current sewage treatment problems in petrochemical enterprises,this paper puts forward Jilin Petrochemical Sewage Monitoring and management system based on large data,and completes the following work:1.Discuss the background of the research,analyze the research status of the system,point out the research purpose and significance of the paper,and finally introduce the work and organization structure of the paper.2.A real-time monitoring technology for large data of sewage is proposed.The clustering effect of large data of sewage is enhanced by using k-means algorithm,and the real-time monitoring of excessive sewage discharge is realized.3.According to the data characteristics of large data and the process of large data processing,the information management system based on Hadoop platform is constructed.The system implements a distributed data processing model composed of multiple nodes,which include core control nodes,data pre-processing nodes,operation nodes and detection control nodes.In practice,it is found that this method can be used in data analysis of sewage monitoring system.4.On the basis of the above-mentioned technology,this paper designs and implements a sewage monitoring system based on large data analysis.The system uses the design idea of MVC for reference and realizes several subsystems,such as factory information management,real-time monitoring management,water quality analysis management,large data analysis and user management.It can not only manage the pollution situation of enterprises comprehensively and intelligently,but also carry on the correlation analysis of large data,and actively promote the construction and development of large environmental data of enterprises.