Studies On Monitoring System And Intelligent Diagnosis Algorithm For Durability Big Data Of Industrial Buildings

Industrial buildings play an important role in industrial production.Due to the harsh environment of industrial buildings,long-term exposure to high temperature,high humidity,corrosive media,durability deteriorates,the use of industrial buildings is lost when the reasonable design life of industrial buildings has not been reached.The safety of industrial production and the safety of people's lives and property will be affected by the durability of industrial buildings.In practice,there are the following problems for existing industrial buildings: the complete durability monitoring system,the data management system,and the real-time intelligent diagnosis of durability are still lacking.In response to the above questions,the research contents are as follows:(1)The wireless remote monitoring system for industrial building durability was designed.The durability monitoring parameters were determined in combination with the production environment of industrial buildings.The overall architecture design,hardware design and software design of the system were carried out,and the remote monitoring of industrial building durability parameters was realized.(2)The main deterioration characteristics of industrial buildings with reinforced concrete structures in general atmospheric environment—the phenomenon of concrete carbonation was analyzed,and its intelligent diagnosis method was studied: a BP-AR based algorithm was proposed to predict the depth of concrete carbonation,according to carbonization.According to the carbonization mechanism,the main influencing factors of concrete carbonation were determined.The BP neural network and time seriesmethod were used to establish the concrete carbonation depth prediction model.The concrete carbonation depth prediction results of BP-AR algorithm and BP neural network were compared and analyzed.The accuracy of carbonization depth prediction using BP-AR algorithm is improved.(3)Hadoop-based industrial building durability big data management information system architecture is designed.The stand-alone mode of Hadoop cluster is established.Distributed file management,calculation and visualization of industrial building durability data are realized by using Hadoop,Hive and Superset.Through the design of industrial building durability wireless monitoring system,concrete carbonization depth prediction and the design of industrial building durability big data platform,the durability intelligent diagnosis and the collection,transmission,management,visualization of industrial building durability data are realized.It is of great significance to predict the service life of industrial buildings and to protect personal and national property.