2023年 05期

摘要(Abstract)：

为了提高pH计校准电压预估精度，提出考虑有色测量噪声的Kalman平滑算法；该算法以电压和电压采集周期作为状态向量，以设定的采样周期和无线pH计所采集的电压值作为观测向量，构建数据融合模型；以考虑有色测量噪声的 Kalman 滤波作为前向滤波，通过马氏距离计算当前时刻最优的有色测量噪声因子，利用Rauch-Tung-Striebel平滑算法对前向滤波的输出值进行平滑，最终得到当前时刻电压的预估值，并将所提出的算法应用于pH计校准电压预估。结果表明，与传统 Kalman 滤波算法相比，所提出的算法的电压预估的精度提高约10%。

关键词(KeyWords)： 数据融合； 电压预估；Kalman 平滑算法；有色测量噪声

基金项目(Foundation): 国家自然科学基金项目(61803175)

作者(Author):邢文芳，拓锐，刘俊聪，刘爱云，徐元

DOI: 10.13349/j.cnki.jdxbn.20230720.002

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