LIU Xiao-dong, TANG Jun-jie, XU Du-feng, et al. Application of Kalman filtering in strain-type force sensor[J]. 2014, 33(7): 147-149+153. DOI: 10.13873/j.1000-97872014.07.044.
卡尔曼滤波在应变式力传感器中的应用
摘要
由于应变式力传感器系统中存在较大的随机噪声
降低了系统的标定精度和测量准确性
而卡尔曼滤波适合实时滤除干扰信号。在建立传感器测试模型基础上
通过推导卡尔曼滤波算法
确定了滤波初值和滤波参数。在传感器—A/D转换器—DSP硬件平台上
进行了滤波算法验证。实验表明:卡尔曼滤波有效地滤除了随机干扰信号
适用于静动态测量过程
提高了系统标定精度。
Abstract
Due to random noise exists in strain-type force sensor system
it reduces calibration precision and measurement accuracy of system
Kalman filtering is suitable for real-time filtering interference signal.On the basis of establishing sensor testing model
through deriving Kalman filtering algorithm
filtering initial value and filtering parameters are determined.On hardware platform of sensor—A /D converter—DSP
filtering algorithm is verified.Experimental results show that Kalman filtering successfully filter random disturbance signal
it is suitable for static and dynamic measurement process