面向水产养殖的水质数据融合方法研究

发布时间：2018-05-25 10:39

本文选题：无线传感器网络 + 数据融合　；参考：《渤海大学》2016年硕士论文

【摘要】：水产养殖的水质优劣直接影响水产品的健康生长,在养殖过程中对水质进行实时监测有助于水产养殖活动的顺利进行。传统的监测方法存在主观性强、耗费时间长和测量参数单一的问题,借助于无线传感器网络和数据融合技术可以实现水质的实时监测。本文依靠水产养殖监测的背景,对无线传感器网络中的数据融合技术进行研究。(1)针对传感器网络中节点数据传输量大、能量消耗快的问题,提出了一种能量均衡的数据融合方法。该方法利用分簇协议将放置于目标区域的传感器分成几个簇,每个簇内选取一个传感器作为簇首节点,将簇首节点的剩余能量和算法执行的轮数作为簇首节点更换的标准,并在簇首节点内对本簇数据进行自适应加权融合,达到均衡各节点能量和减少数据传输量的目的。(2)针对传统养殖水质监测方法无法为养殖用户提供实时、准确的水质信息的问题,提出在养殖水域搭建无线传感器网络,利用智能传感器采集水质的参数信息,并将能量均衡的数据融合方法应用到采集过程中。无线传感器网络每半个小时进行一次数据采集工作,保障了数据的及时性,节点采集的源数据经过分类加权融合后提高了数据的准确性。(3)利用MATLAB平台对水域中的PH值、水温、溶氧量三种参数进行融合仿真实验,结果表明水质融合算法可以有效地综合各节点采集的数据,得出准确性高的参数估计值。
[Abstract]:The quality of aquaculture directly affects the healthy growth of aquatic products, and real-time monitoring of water quality in the process of aquaculture is conducive to the smooth progress of aquaculture activities. The traditional monitoring methods have the problems of strong subjectivity, long time consumption and single measurement parameters. With the help of wireless sensor networks and data fusion technology, real-time monitoring of water quality can be realized. In this paper, based on the background of aquaculture monitoring, the data fusion technology in wireless sensor networks (WSN) is studied. A data fusion method for energy balance is proposed. In this method, the sensors placed in the target region are divided into several clusters by clustering protocol. One sensor is selected as the cluster head node in each cluster, and the residual energy of the cluster head node and the number of wheels executed by the algorithm are taken as the standard for the cluster head node replacement. In order to balance the energy of each node and reduce the amount of data transmission, the cluster data can be adaptively weighted and fused in the cluster head node. The problem of accurate water quality information is discussed. A wireless sensor network is set up in the aquiculture area. The intelligent sensor is used to collect the parameter information of water quality, and the data fusion method of energy balance is applied to the acquisition process. Wireless sensor network carries out data acquisition every half hour to ensure the timeliness of data. After classified and weighted fusion, the source data collected by nodes can improve the accuracy of the data. (3) using MATLAB platform, the PH value and water temperature in water area are improved. The results show that the fusion algorithm can effectively synthesize the data collected by each node and obtain the accurate parameter estimation.
【学位授予单位】：渤海大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP202

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