基于时空数据融合理论的冷链温度监控系统

摘要

针对易腐农产品冷链物流过程中温度传感器所采集的大量数据，提出时间-空间数据融合理论，并将之应用于易腐农产品冷链物流温度监控系统中，使采集数据能准确地反映冷藏车厢运行状况。首先，对单传感器采用分批估计方法，按照时间先后对观测值进行数据融合，得到每个传感器的局部温度估计值；然后，对单个传感器局部估计值采用自适应调节各传感器权重的方法，对位于空间不同位置的传感器进行数据融合，从而得到冷链车厢监测温度的最终融合值，以期获得比有限个传感器的算术平均值更准确和更可靠的测量结果，以提高信息收集的效率，实现网络节能。数据分析表明，处理后的数据更接近测量真实值。%This paper presents a new data fusion algorithm based on time -space fusion theory for perishable food cold chain monitoring system .Firstly , the data of single sensor is fused according to the time order by means of batch estima-tion method in order to get the partial temperature value .Then , the variance of partial temperature value and the final fu-sion valve is used to adaptively adjust the weight of each sensor , and the ultimate fusion value is obtained .The algorithm can make the performance calculation result reflect the refrigerator van ’ s real status well and truly , which is simple and reliable.Compared with arithmetic means of finite sensors , it can obtain more exacter measuring result .The algorithm can also reflect redundancy or complementary information of multi-sensor in space or time .