【摘要】 针对光栅传感网络数据加权融合中出现异常值会导致融合结果偏差较大的问题,在分析光栅传感系统中的噪声和干扰后,提出一种改进的自适应加权融合算法.该算法适用于观测数据不满足正态分布的情况,先对原始数据进行截尾加权融合,再以截尾融合结果代替异常值进行加权最小均方差融合,既充分利用了传感数据,也降低了融合算法的复杂度.在光纤光栅温度传感网络实验中使用该算法,其输出方差为0.083 9,小于加权最小均方误差算法方差0.383 9和截尾加权算法方差0.254 2,证实了该算法可行性.更多还原

【Abstract】 To deal with outliers caused by noise and disturbance during weighted fusion of Fiber Bragg Grating(FBG) temperature sensing network resulting in augmenting error,an improved adaptable weighted fusion algorithm is presented after analysing nosie and interference in FBG sensing system.This algorithm is suitable for sensing data processing which don’t obey normal distribution.Firstly,Trimmed Mean Weighted(TMW) algorithm is used to process multisensor data fusion,and then replace outliers with the fusion result of TMW algorithm,finally Weighted Minimum Mean Square Error(WMMSE) algorithm is used to process twice-fusion,here data are fully used and complexity of algorithm are obviously reduced.New algorithm is applied in fiber Bragg grating temperature sensing,output’s variance 0.083 9 less than WMMSE algorithm’s variance 0.383 9 and TMW algorithm’s variance 0.254 2,correctness and accuracy are testified.更多还原