Research And Application Of Data Processing Methods For Detection And Monitoring Of Typical Industrial Equipment

Industrial equipment is the foundation and support for industrial development.In recent years,with the development of cloud computing,Internet of Things and other technologies,new methods and models have been provided for the detection and monitoring of typical industrial equipment.The thesis detects and monitors the health status of industrial equipment,realizes the data collection of industrial equipment operation status and process status through the Internet of Things technology,and uses the big data technology to solve the distributed storage and calculation of the massive industrial data collected,so as to realize the intelligent management of the equipment.The thesis designs and implements a set of equipment health detection and monitoring system applied to industrial equipment.Effectively reduce the safety production accidents caused by the equipment,increase the mission life of the equipment,increase the utilization rate of resources,and exert the safety support role of industrial equipment in industrial development.The thesis mainly completed the following work:Analyzed the related technologies used by the big data platform of industrial equipment,including the characteristics analysis of big data,HDFS and HBase technology of distributed data storage,Spark technology of distributed computing,Zookeeper of big data technology and big data visualization technology.Relevant research on industrial equipment inspection and monitoring of big data storage and big data computing was carried out,comparative analysis of different big data storage and computing architectures was carried out,and the big data storage and computing architecture were optimized and verified.Put forward the overall design plan of the big data processing platform for typical industrial equipment health detection and monitoring,and conduct demand analysis,overall platform design,data acquisition layer design,data storage layer design,data calculation layer design and application visualization layer design.Completed the implementation of the big data processing platform for health detection and monitoring of typical industrial equipment.Based on HDFS + HBase +Spark technology,Alibaba Cloud was adopted to implement the distributed deployment of big data storage and computing modules to complete the core storage and computing functions of the platform.The two main application requirements of the platform are realized: periodic detection of industrial equipment and real-time monitoring of equipment,and the realization of the module functional design of the platform,including: big data acquisition,big data storage,big data calculation,big data application and so on,and realized the visual display of the corresponding big data.