摘要
针对热式质量流量计测量过程中模数转化器(ADC)对传感器采集的电信号转化过程中,由于器件本身的系统误差和输入信号、外部电路引起的噪声误差导致的转化的数字量偏离理论值且不断波动的问题。提出了一种基于改进卡尔曼(Kalman)算法的软件滤波方法,在消除误差的同时提高Kalman算法收敛速度,并通过概率统计的方法对数据误差建立概率分布模型,为Kalman参数的选择提供理论依据。最后在FPGA上实现该算法并进行试验验证,相较于滤波前的数据,平均误差由1.81%降低至0.82%,数据波动控制在2 LSB范围内。结果表明该方法能有效消除误差,提高测量系统的稳定性。
In the measurement process of thermal mass flowmeter, due to the systematic error of analog-to-digital converter(ADC) itself, and the influence of input signal and external circuit noise, the digital quantity signal transformed by ADC will deviate from the theoretical value and constantly fluctuate. Therefore, we propose a software filtering method based on the improved Kalman algorithm, which can improve the convergence speed of Kalman algorithm while eliminating the error. In addition, the probability distribution model of data error is established by probability statistics method, which provides theoretical basis for Kalman parameter selection. Finally, the algorithm is implemented on FPGA and verified by experiments. Compared with the data before filtering, the average error is reduced from 1.81% to 0.82%, and the data fluctuation is less than 2 LSB.The results show that the method can effectively eliminate errors and improve the stability of the measurement system.
作者
刘宁庄
戴伟
Liu Ningzhuang;Dai Wei(School of Electrical and Control Engineering,Xi'an University of Science and Technology,Xian 710062,China)
出处
《电子测量技术》
北大核心
2022年第15期172-177,共6页
Electronic Measurement Technology
基金
国家自然科学基金(12074354)项目资助。
