Signal Iterative Search Method Based on Kalman Filter for Vortex Flowmeter

Vortex flowmeters measure the fluid flow rate using the principle of fluid oscillation, making the measurement process susceptible to external vibration. Therefore, the research on anti-vibration signal processing of vortex flowmeters is of great significance. Based on a large number of experiments, an iterative search method based on the Kalman filter for vortex flowmeter (hereinafter referred to as ISKF) is proposed innovatively. First, the mathematical models of vortex flow signal and interference are constructed. According to the mathematical model, the interference is characterized as white Gaussian noise, periodic vibration interference, and transient impact interference. Then a Kalman filter-based vortex flow system model is created to eliminate the white Gaussian noise by linearizing the vortex flow signal model. For the periodic vibration, an iterative search criterion is designed based on the amplitude-frequency relationship of the vortex flow signal. Finally, offline and online experiments are conducted on the gas experimental setup. The experimental results show that the ISKF method can better overcome periodic vibration and transient impact interference. In general, this article lays a solid theoretical foundation for the commercialization of a new type of anti-vibration flowmeter.