基于数据融合的仓储环境远程监控系统研究

发布时间：2019-01-04 10:50

【摘要】：随着我国经济的快速发展,现代企业和物流业对仓储系统的要求越来越高。仓库温湿度及其他环境因素的变化将会对货物地存储和运输造成极大的影响。传统的仓储环境监控系统需要管理人员亲临现场进行记录和查看设备运行状况,监测手段单一,测量数据不精准,数据管理和利用效率低下。而新兴仓储环境监测系统结合远程监控技术和计算机网络技术有效避免了上述弊端,同时该系统还具有简单、高效、跨平台等优点,已经成为一种广泛应用的信息交互平台。本文提出了一种基于数据融合的多传感器仓储环境远程监控系统,该系统以Web相关技术为基础,通过ZigBee无线网络传递仓库的实时温度、湿度和光照度等数据,并采用多传感器自适应加权融合算法对这些数据进行融合估计处理,提高测量数据的精度。最终实现在不需要到达监控现场的情况下,就可以对环境监测数据完成查询、管理、智能决策等功能。论文首先介绍了课题研究的背景和意义,阐述了仓储环境远程监控系统的国内外研究现状,设计了系统总体结构。其次引入数据融合的相关概念和算法,对多个传感器采集到的原始数据进行估计处理,通过多种算法的对比,确定多传感器自适应加权融合算法为本系统主要的融合方式,达到提高观测数据的精准性、减少冗余数据、提高网络传输速率的目的,并通过MATLAB验证了其适用性。仓储环境远程监控系统主要分为现场监控系统和远端监控系统,本文完成Internet环境下B/S模式的远端系统开发,对系统的体系结构、软件实现技术等做了深入调查和研究。阐述了仓储环境远程监控系统的需求分析、开发流程、总体框架以及各个模块的实现过程。介绍了系统的软件开发平台和开发语言。实现了实时查询、下载、对远程设备进行控制等功能。
[Abstract]:With the rapid development of economy in China, modern enterprises and logistics industry are demanding more and more storage system. Changes in warehouse temperature, humidity and other environmental factors will greatly affect the storage and transportation of goods. The traditional warehousing environment monitoring system requires managers to record and view the operation of the equipment in person. The monitoring method is single, the measurement data is not accurate, and the efficiency of data management and utilization is low. The emerging warehouse environment monitoring system combined with remote monitoring technology and computer network technology effectively avoids the above disadvantages. At the same time, the system has the advantages of simple, efficient, cross-platform, and has become a widely used information exchange platform. A remote monitoring system based on data fusion for multi-sensor storage environment is proposed in this paper. Based on Web technology, the real-time temperature, humidity and illumination of warehouse are transmitted through ZigBee wireless network. The multi-sensor adaptive weighted fusion algorithm is used to estimate these data to improve the accuracy of measurement data. Finally, the functions of query, management, intelligent decision and so on can be completed without the need to reach the monitoring site. Firstly, this paper introduces the background and significance of the research, expounds the present situation of the remote monitoring system of storage environment at home and abroad, and designs the overall structure of the system. Secondly, by introducing the related concepts and algorithms of data fusion, the original data collected by multiple sensors are estimated and processed. Through the comparison of various algorithms, it is determined that the multi-sensor adaptive weighted fusion algorithm is the main fusion method of the system. It can improve the accuracy of observation data, reduce the redundant data and improve the transmission rate of the network. The applicability of the method is verified by MATLAB. The remote monitoring system in storage environment is mainly divided into field monitoring system and remote monitoring system. This paper completes the development of remote system based on B / S mode in Internet environment, and makes a thorough investigation and research on the system architecture and software implementation technology. The requirement analysis, development process, overall framework and the realization process of each module of remote monitoring system in storage environment are described. The software development platform and development language of the system are introduced. Realized real-time query, download, remote equipment control and other functions.
【学位授予单位】：广西师范大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP277;TP202

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