P‐8.5: Research on Flowmeter Signal Processing Method Based on Improved Kalman Filterust

Flowmeter is an instrument for measuring the flow rate of fluid, which is widely used in industrial, agricultural, environmental and other fields. However, the signal of flowmeter is often affected by various noises and interferences, which reduces the measurement accuracy. In order to improve the signal quality of flowmeter, this paper proposes a flowmeter signal processing method based on adaptive Kalman filter. This method uses the advantages of Kalman filter, combined with adaptive algorithm, dynamically adjusts the process noise covariance matrix and measurement noise covariance matrix, and realizes the effective filtering and estimation of flowmeter signal. This research takes the water flow signal processing based on Kalman filter as an example, and verifies the effectiveness and superiority of this method through simulation and experiment. The results show that this method can effectively suppress the noise and interference in the flowmeter signal, improve the measurement accuracy and stability of the flowmeter, and is suitable for different working conditions and different types of flowmeters.