矿用无线监测数据融合估计方法研究
Research of Data Fusion Estimation Algorithm in Mine Wireless
随着物联网的研究热潮,传感器网络逐渐深入到工业应用中。其中,基于统计估计方法的信息数据融合是无线传感器网络的在矿山的重要应用之一。本文分析和总结了目前无线传感器网络中适宜矿山应用的数据融合统计估计方法,针对矿山的无线传感器网络的特点,总结并拓展了数据融合的基本模型,梳理和归纳了数据融合处理的主要方法,并讨论了在当前阶段的技术发展趋势和挑战。
Along with the upsurge of Internet of Things(IoT) research, there are much research focus on the sensing network which is gradually introduced into industry applications. Among these applications, Data fusion that depends on statistic estimation is one of important applications in sensor network. We summarize estimation methods which are better for mine industry application. Then, we analyze the special characters of the sensor network in mine industry and discuss some models of sensor network. Moreover, we review and summarize the statistic estimation methods of data fusion that used in sensors network, especially in mine industry sensors network. At last, we present and discuss the challenges for the current research of statistic estimation approach of data fusion in mine industry sensor network.
缪协兴、张艳群、鲍宇
矿业工程理论与方法论无线通信电子技术应用
无线传感器网络,矿山物联网,数据融合统计估计方法
Wireless sensors networks Mine Internet of things Data fusion estimation algorithm
缪协兴,张艳群,鲍宇.矿用无线监测数据融合估计方法研究[EB/OL].(2014-07-29)[2025-08-18].http://www.paper.edu.cn/releasepaper/content/201407-341.点此复制
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