压缩感知技术在矿山物联网中的应用研究_中国煤炭行业知识服务平台

压缩感知技术在矿山物联网中的应用研究

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Title

Applied study on compressed sensing technology to mine internet of things
作者

赵小虎邓园芳慕灯聪
Author

Zhao Xiaohu Deng Yuanfang Mu Dengcong
单位

中国矿业大学物联网（感知矿山）研究中心中国矿业大学信息与电气工程学院
Organization

Research Center of lnternet of Things ( Perception Mine) ,China University of Mining and Technology School of lnformation and Electrical Engineering,China University of Mining and Technology
摘要

针对矿山井下环境的特殊性导致井下监测到的海量信息的获取受到限制等问题,对目前备受关注的基于信号稀疏性的新型采样理论——压缩感知理论进行研究,以矿山物联网为研究对象,介绍了压缩感知基本理论及关键技术,分析了压缩感知理论在这个应用环境中的优势,理论上满足矿山物联网应用的需求。最后,利用Matlab仿真软件,对煤矿井下采集到的瓦斯浓度数据进行稀疏性分析、压缩与重构,结果表明压缩感知技术可以较精确地恢复原始瓦斯浓度信号。
Abstract

According to a specality of underground mine environment to cause problem ofthe limitaion to obtain mss information measured in underground mineand others a study was conducted on the present concerned compressed sensing theor - a new samping theory based on the signal sparityBased on mine inermet ofthings as studly object.the paper inroduced basic theory and key technolgy of the compressed sensing and analyzed advantages ofthe compressed sensing theory inaplcatin environment.Thecetcally the compressed sensing theory could mee application reqxuirements of mine intenet of thigs.Fmal ythe Matiab sinulaton sofware was applied to sparsity analysis compression and reconstruction ofthe gas concentration datacollctedfrom underground mine and the rsulis shoved that ofginaconcentration signal could be accurately recovered by compressed sensing technology.
关键词

矿山物联网互联网+压缩感知稀疏性观测矩阵:瓦斯浓度数据
KeyWords

mine internet of things;internet plus; compressed sensing; sparsity; observation matrix; gas concentration data;
基金项目(Foundation)

中央高校基本科研业务费专项资金资助项目(2014ZDPY19)；国家重点研发计划资助项目(2016YFC0801405)；
相关文章

[1]论感知矿山物联网与矿山综合自动化
[2]基于CS架构的煤矿井下图像处理算法研究
相关专题

这篇文章属于矿山“互联网+”技术研究与应用（23篇）