摘要
针对多变量耦合的猪舍环境,采用自适应加权算法和D-S证据推理算法相结合的方法,提出一种适用于猪舍环境监测的分布式多传感器体系结构和二级融合模型,对多传感器采集的温度、湿度和光照度信息进行融合,克服了单传感器带来的不确定性和不稳定性,增强了多传感器信息融合系统的鲁棒性。结果表明,这种方法提高了猪舍环境检测的准确度。
Aimed at multi-variable coupled piggery environment, a method which combines self-adaptive weighting algorithm with D-S evidential reasoning algorithm is used. A distributed multi-sensor architecture and two-level fusion model for piggery environment monitoring is presented. This method of fusing temperature, humidity and light intensity from different sensors overcomes uncertainty and instability from single-sensor and enhances multisensor information system＇ s fault-tolerance and robustness. The result indicates that this method improves the accuracy of the detection of piggery environment.
出处
《传感器与微系统》
CSCD
北大核心
2009年第12期109-112,共4页
Transducer and Microsystem Technologies
关键词
多传感器数据融合
猪舍环境
二级融合
multi-sensor data fusion
piggery environment
two-level fusion
