跟踪(教育)
卡尔曼滤波器
滤波器(信号处理)
干扰(通信)
信号(编程语言)
相(物质)
计算机科学
控制理论(社会学)
流量测量
准确度和精密度
算法
声学
数学
物理
统计
人工智能
计算机视觉
机械
电信
控制(管理)
心理学
教育学
频道(广播)
程序设计语言
量子力学
作者
Nan Chen,Shangchun Fan,Dezhi Zheng
摘要
In order to improve the measurement accuracy of Coriolis mass flowmeters, this paper investigates the possible application of a strong tracking filter during signal processing. Specifically, a novel phase difference measurement method, based on a strong tracking filter for Coriolis mass flowmeters, is proposed in order to overcome the problems associated with the extended Kalman filters, which cannot accurately track time-varying phase differences. Compared with the existing methods, the proposed method can continuously track phase difference variation with high precision. The proposed method is a parallel algorithm that does not need to predict signal frequency in advance; this can effectively eliminate the quadratic error associated with frequency estimation. The results of simulation and experiments verify the proposed method that has better estimation performance and enhances the anti-interference performance of phase difference estimation, which contributes to improving the measurement accuracy of Coriolis mass flowmeters.
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