木材干燥窑内温度检测的自适应加权融合方法研究

Adaptive Weighted Fusion Method for Detecting Wood Drying Kiln Temperature

[目的]研究木材干燥窑内多点温度数据处理方法。[方法]在数据融合的基础上提出基于多传感器自适应加权两级融合估计方法。该算法在不知道传感器测量数据先验概率分布知识的条件下,可以从含有噪声的测量数据中得到被估计量的最小均方误差估计。[结果]将自适应加权两级融合方法应用在木材干燥窑温度检测系统中,有效提高了干燥窑内温度的检测精度,优于通常检测窑内温度时采用算术平均值的方法。[结论]该算法实时性好,只依靠当前的测量数据就可以融合估计出总均方误差最小的估计值,对研究数据融合技术和木材干燥工艺具有重要的意义。

[ Objective] This research is aiming at the data processing method of multi-point temperature in wood drying kiln. [ Method] Based on the data fusion, this paper proposes a multi-sensor adaptive weighted dual-fusion method. In the condition of unknowing the sensor meas- urement data prior knowledge of the probability distribution, this algorithm could get minimum mean square error estimation within noise data. [ Result] The method could improve the detection precisely and get better effect than arithmetic mean which is Wildly used. [ Conclusion] This algorithm that maintain the character of good-real-time could estimate total minimum mean square error by using present detection data, and has significance for data fusion and wood drying technology.