Research On Signal Processing Method Of Electromagnetic Flowmeter Based On Improved Kalman Filter

Electromagnetic flowmeter(EMF)is widely used in the water flow measurement and solid-liquid two-phase flow measurement,for no obstructions and moving parts in measuring tube.The measurement accuracy of EMF is determined by its excitation mode and signal processing method.Existing signal processing methods have the problems of limited applicability and slow dynamic response speed,due to the limitation of filter bandwidth and large amount of calculation.Therefore,according to the time domain characteristics of the output signal of EMF sensor,a signal processing method is proposed,which has strong applicability,high measurement accuracy and fast dynamic response speed.According to the time-domain characteristics of constant flow demodulation sequence,the ARMA model of constant flow demodulation sequence is established by using time series analysis method.According to the velocity variation law in variable flow process,the Logistic model of demodulation sequence in variable flow section is established.According to the constant flow demodulation sequence model,the state space expression of the demodulation result of EMF is established,and the Kalman filter method is used to process the demodulation result.Aiming at the problem that the traditional Kalman filter can’t follow flow change quickly in variable flow measurement,the statistical characteristics of filtering results are analyzed,and a residual judgment based improved Kalman filter method is proposed.During solid-liquid two-phase flow measurement,in order to solve the problem that the residual error becomes larger and the velocity state is misjudged,a differential judgment based improved Kalman filter method is proposed.This method and the existing signal processing methods are used to process the water flow signal and the four solid-liquid two-phase flow(pulp,PVC particle slurry,sawdust,and coal water slurry)signals respectively.Results show that the steady-state volatility and dynamic response time of the differential judgment based improved Kalman filtering method are smaller,which verifies the effectiveness of the proposed method.Based on the hardware systems of rectangular wave excitation electromagnetic flowmeter(REMF)and high frequency resonant sine wave excitation electromagnetic flowmeter(SEMF)in laboratory,the differential judgment based improved Kalman filtering method is realized.The developed system is matched with DN40 EMF sensor to carry out water flow calibration experiment and dynamic response speed experiment.Water flow calibration results of REMF(6.25Hz and 12.5Hz)and SEMF(75Hz and 145Hz)show that,when flow volume range is 2.3m~3/h～23m~3/h,the measurement error is within±0.5%,and the repeatability is not higher than 0.15%,and the accuracy level of the system is 0.5.Dynamic water flow response time experimental results are as follows:6.25Hz REMF,less than 2s;12.5Hz REMF,less than 1.5s;75Hz SEMF,less than 2.5s;145Hz SEMF,less than 1.6s.