Big Data Analysis And Visualization Of Industrial Internet Of Things For Analog Systems

With the advancement of technology,and the new generation of industrial,the application of sensor devices is more extensive,and the amount of data generated has also increased exponentially.People have gradually moved toward the era of industrial big data.A large amount of data has emerged,the Industrial Internet of Things faces challenges in various aspects such as massive data storage,fast query and data mining analysis.It is necessary to find effective processing methods for industrial data applications.According to the actual needs analysis of the project,this paper systematically studied the characteristics of industrial IoT big data,and combined the existing big data processing tools to design the big data query and analysis system of Industrial Internet of Things.The history data of the operation of the heat exchange station which is in the intelligent factory is queried and analyzed in this system.Adopted a three-tier architecture,the bottom layer is the data layer,which is mainly responsible for the collection of sensor data of the Internet of Things terminals,and used Hive as a data warehouse.The computing layer mainly provides a computing framework.By using the open source SQL query engine,named Presto,build a cluster computing environment,which is based on memory computing,and parallelization of data computing is realized.The top-level interaction layer is responsible for the application of data analysis and the generation of results,for the interaction between the system and the user,receiving and forwarding the query request submitted by browsers,the query task is transmitted to the server cluster for execution,and the final query result displayed to the user in the form of the browser.On the user system,realized the statistical query and fitting analysis of the historical data collected by sensor.According to the historical operation data in heat exchange station,analyzed the correlation relationship among supply water temperature,return water temperature and outdoor temperature,and realized the visualization of the data analysis.