基于分簇数据融合的农产品冷链温度监控方法

发布时间：2018-04-18 19:56

本文选题：WSN无线传感网 + 分簇融合　；参考：《农业机械学报》2017年08期

【摘要】：针对现有基于无线传感网络的农产品冷链物流监测系统,传感器节点数据传输量大,带宽利用率低、能耗高,网络生命周期短的问题,提出了一种基于算术平均值与分批估计的簇内数据融合及自适应加权的簇间数据融合冷链温度监测方法。首先利用疏失误差对采集数据进行预处理,然后利用平均值与分批估计方法对簇成员节点发送的数据进行融合处理,最后簇头节点利用自适应加权算法对接收到的成员节点数据进行进一步的融合处理。实验证明,基于该数据融合方法的冷链监测系统网络生存周期相比传统方法提高了34.2%,稳定周期相比于传统低功耗自适应集簇分层型协议提高了11.4%,数据融合精度高于传统算术平均值法7.6%,系统能耗每轮降低约32.5%。能够有效降低冗余和可信度较差的数据对测量结果带来的影响,减少不必要数据传输损耗,降低了冷链物流成本,提高了农产品冷链物流信息化程度。
[Abstract]:In view of the existing cold chain logistics monitoring system of agricultural products based on wireless sensor network, the sensor node has a large amount of data transmission, low bandwidth utilization, high energy consumption, and short network life cycle.Based on arithmetic mean and batch estimation, a cold chain temperature monitoring method based on intra-cluster data fusion and adaptive weighted data fusion is proposed.Firstly, the collected data is preprocessed by the error of error, and then the data sent by the cluster member node is fused by the method of average value and batch estimation.Finally, the cluster head node uses adaptive weighting algorithm to further fuse the received member node data.Experiments prove that,Compared with traditional methods, the network lifetime of cold chain monitoring system based on this data fusion method is increased by 34.2um, and the stable cycle is improved by 11.4than that of traditional low-power adaptive cluster-based hierarchical protocols. The accuracy of data fusion is higher than that of traditional arithmetic.With the average value of 7.6, the energy consumption of the system is reduced by about 32.5 per round.It can effectively reduce the impact of redundant and less reliable data on the measurement results, reduce the unnecessary data transmission loss, reduce the cold chain logistics costs, and improve the degree of agricultural cold chain logistics information.
【作者单位】：石河子大学信息科学与技术学院;中国农业大学信息与电气工程学院;
【基金】：国家自然科学基金项目(71261021)
【分类号】：TN929.5;TP212.9;TP274

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