压缩感知技术在矿山物联网中的应用研究
Applied study on compressed sensing technology to mine internet of things
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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.