【作者】 曾杰；

【导师】 杨正益；

【作者基本信息】 重庆大学 ， 工程（软件工程）（专业学位）， 2020， 硕士

【摘要】 工业设备是工业发展的基础和支撑,近年来,随着云计算、物联网等技术的发展,为典型工业设备的检测监测提供了新方法和新模式。论文针对工业设备健康状况进行检测监测,通过物联网技术实现工业设备运行状态及工艺状态的数据采集,用大数据技术解决采集到的海量工业数据分布式存储与计算问题,从而实现设备的智能管理。论文设计并实现了一套运用于工业设备的设备健康检测监测系统。有效地减少因设备导致的安全生产事故,增加设备的使命寿命,提高资源的利用率,发挥工业设备在工业发展中的安全支撑作用。论文主要完成了以下工作:(1)分析了工业设备大数据平台所使用的相关技术,包括大数据的特征分析,分布式数据存储的HDFS及HBase技术以及分布式计算的Spark技术,大数据技术Zookeeper以及大数据可视化技术。(2)针对工业设备检测监测大数据存储与大数据计算展开了相关的研究,对不同的大数据存储与计算架构展开了对比分析,进行了大数据存储及计算架构的优化设计,并进行了验证。(3)提出了面向典型工业设备健康检测监测大数据处理平台的总体设计方案,进行了需求分析、平台总体设计、数据采集层设计、数据存储层设计、数据计算层设计及应用可视化层设计。(4)完成了面向典型工业设备健康检测监测大数据处理平台的实现,基于HDFS+HBase+Spark技术,采用阿里云,对大数据存储与计算模块的分布式部署,完成平台核心的存储与计算功能,实现了平台的两个主要的应用需求即对工业设备的周期性检测与对设备的实时监测,实现了平台的模块功能设计,包括:大数据采集、大数据存储、大数据计算、大数据应用等,并实现了相应的大数据可视化展示。更多还原

【Abstract】 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.更多还原