基于卡尔曼滤波的电磁流量计信号处理

针对电磁流量计在强干扰条件下测量精度不高的问题,提出了基于残差的卡尔曼滤波方法提高电磁流量计的精度。 采 用滑动平均滤波器对实验数据进行预处理,降低测量时电磁流量计测量时受到强干扰噪声的影响。 分析电磁流量计在固井过 程中的受干扰情况,提出基于残差的卡尔曼滤波的方法,实现过程噪声协方差 Q 随流量变化快速切换,提高卡尔曼滤波的响应 速度。 实验结果表明,经过上述算法处理后定流量下的不确定度降低了 14. 6% ~ 22. 6%,流量发生变化时的响应时间减少 5 ~ 18 s,同时测量累积排量精度达到 0. 12%,满足固井工程施工要求。 本文所设计的滤波算法有效降低噪声影响,使测量结果更 加稳定可靠。

Kalman filter-based electromagnetic flowmeter signal processing

The Kalman filter method based on residuals is proposed to improve the accuracy of electromagnetic flowmeter for the problem of poor measurement accuracy under strong interference conditions. In this paper, a sliding average filter is used to pre-process the experimental data and reduce the impact of strong interference noise on the electromagnetic flowmeter measurement during measurement. Analysis of the electromagnetic flowmeter in the process of solidification by the interference, the proposed residual-based Kalman filtering method to achieve process noise covariance Q with the flow rate changes quickly switch, to improve the response speed of Kalman filtering. The experimental results show that the uncertainty at constant flow rate is reduced by 14. 6% to 22. 6% and the response time is reduced by 5 to 18 seconds when the flow rate changes after the above algorithm processing. At the same time, the accuracy of measuring cumulative displacement reaches 0. 12%, meeting the construction requirements of solidification projects. The filtering algorithm designed in this paper effectively reduces the influence of noise and makes the measurement results more stable and reliable.