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.