卡尔曼滤波在应变式力传感器中的应用

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。

Application of Kalman filtering in strain-type force sensor

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,and improve calibrating precision of system.