基于物联网的黄河含沙量数据融合技术研究  

Study of data fusion technique for measuring Yellow River sediment based on Internet of Things

作　　者：刘明堂[1] 司孝平[1] 

机构地区：[1]华北水利水电学院信息工程学院,河南郑州450011

出　　处：《泥沙研究》2012年第4期6-10,共5页Journal of Sediment Research

基　　金：水利部黄河泥沙重点实验室开放课题基金项目(2012005);河南省教育厅2009年度自然科学研究项目(2009B510013)

摘　　要：针对黄河流域含沙量检测的实际要求,研究了多传感器数据融合技术,尤其是多元线性回归分析的数据融合技术,建立了基于物联网的黄河含沙量在线检测系统。系统将分散在物联网上的水温、深度和流速等传感器集成起来,综合考虑环境因素来测量黄河流域上的含沙量。试验结果表明,利用分布在物联网上的多传感器进行信息采集,并进行数据融合处理,能减小因环境因素带来的误差,提高含沙量检测的精度,增强系统的稳定性。To meet the requirement of sediment measurement in the Yellow River,data fusion techniques for multi-sensor,especially the technique based on multiple linear regression,are studied.The online measurement system of the Yellow River is architectured based on the Internet of Things（IOT）.Considering the environment factors in this system,the water temperature,water depth and velocity sensors in the Internet of Things are integrated to measure the sediment concentration.Experiment results show that the multi-sensor data fusion technology can reduce the errors induced by environmental factors,improve the detection accuracy and enhance the stability by collecting the online multi-sensor information and data fusion on the Internet of Things.

关 键 词：物联网 含沙量检测 多传感器 数据融合 多元线性回归 

分 类 号：P333.4[天文地球—水文科学]