Studies And Implementation Of Signal Processing Methods For Electromagnetic Flow Sensor In Slurry Flow Measurement

With the structural characteristics of no moving parts or hindering fluid components, electromagnetic flowmeter (EMF) has been successfully applied to the measurement of solid-liquid slurries, such as coal slurry, paper slurry and Alumina slurry. But during slurry flow measurement, the non-stationary slurry noise is generated when solid particles scratch the electrodes of EMF. This kind of undesired noise is superimposed on the normal flow rate signal, and leads to large fluctuation and big error in the measurement result. For the problem of slurry measurement of EMF, some foreign companies proposed their solutions and developed the EMF with the function of slurry flow measurement. But they did not disclose the specific technical details, and the Chinese companies still cannot solve the technical problems. For this reason, this paper does the research into slurry flow signal processing methods and its implementation for EMF in slurry flow measurement.According to the slurry experimental signals, the probability function model is build up for demodulation results of slurry flow signals from EMF. Because of their randomness and non-stationary probability property, slurry flow signals are demodulated firstly, and then the probability density of their demodulated amplitude is calculated. Fitting results show that probability density function (PDF) of amplitude demodulation of slurry flow signal obeys non-Gauss a stable distribution.The statistical reconstruction based signal processing method is proposed for slurry signal processing of EMF. According to the non-Gauss a stable distribution, slurry flow signals are demodulated firstly. Then the demodulated results are processed with non-linear median filtering method to eliminate slurry noise, and the filtered results are used to reconstruct "de-noised" flow signal. Finally the reconstructed flow signal is filtered with a comb-band pass filter for further eliminating interferences.The wavelet decomposition and reconstruction based signal processing method is proposed for slurry signal processing of EMF. Firstly slurry flow signals are decomposed through stationary Haar wavelet transform (SWT) into detail coefficients and approximate coefficients. According to the periodic feature of detail coefficients, the detail coefficients are extracted to form the same-phase sequences. As the PDF of same-phase sequences from detail coefficients follows a stable distribution, the detail coefficients are firstly decomposed into same-phase sequences, and then the same-phase sequences are processed with non-linear median filtering method to eliminate slurry noise. Approximate coefficients are processed with notch filtering method to extract out the leakage signal components. Then the notch filtering results are decomposed into same-phase sequences and processed with non-linear median filtering method to eliminate slurry noise. Finally, the filtered detail coefficients and filtered approximate coefficients are united into stationary Haar wavelet reconstruction. Thus the complete separation of flow signal and non-stationary slurry noise is realized.The differential pretreatment based signal processing method is proposed for slurry signal processing of EMF. In order to stabilize slurry flow signal to the vicinity of OV, slurry flow signals are firstly processed with one-order differential pretreatment or the half cycle differential pretreatment. As the same-phase sequences from differential results follow a stable distribution, the differential results are firstly decomposed into same-phase sequences and then processed with non-linear median filtering method. Filtering results of half cycle differential signals are the separated flow signals. Filtering results of one-order differential signals are processed with a comb-band pass filter to eliminate low frequency drift. Finally the calculated results are processed with one-order integration of initial value0to reconstruct the flow signal.The velocity variation feature and changeable window based dynamic flowrate following method is proposed for slurry signal processing method of EMF. The slurry flow signals are filtered by non-linear filtering method with large window parameters and small window parameters simultaneously. The difference between two filtering results are taken as the velocity variation feature and the determine conditions are decided accordingly. If system judges that flowrate is changing, filtering results with small window parameters are outputted. When system determines flowrate is stable, filtering results with large window parameters are outputted. In this way the output results of slurry flow signal processing system has the characteristic of both small fluctuation rate at stable flow and the fast following speed at changing flow.A DSP based slurry signal processing system of EMF is developed. Based on the hardware system of EMF, the statistical reconstruction based slurry flow signal processing method and the comb-band pass filter based water flow signal processing algorithm are both realized. The developed system has the empty pipe detection function during power-on process and normal measurement process. The developed system adopts the threshold control based bias adjustment method, and does the correction of current output module and pulse output module, which improves the accuracy of the output module. Water flow calibration results show that the calibration accuracy of our developed water flow measurement system is better than0.5%and its repeatability is better than0.1, during flowrate from0.25to10m/s.A solid-liquid two-phase flow experimental set up for EMF is designed. In order to evaluate the developed slurry signal processing system of EMF, the solid-liquid two-phase flow experimental set up is designed in this paper, which can enable the standard meter calibration, standard volume calibration and standard weighing method calibration of EMF. Based on this experimental set up, the developed slurry signal processing system is connected with EMF sensor made by Yokogawa and EMF sensor made by Shanghai Yinuo Instrument Co., Ltd. separately. Together with the standard EMF meter from Germany Krohne Company, the water flow standard weighing method calibration, paper slurry standard weighing method calibration and PVC solid slurry comparative experiments of the developed slurry signal processing system are conducted. Experimental results show that response time of the developed slurry signal processing system is considerable to Krohne EMF. The developed system has better performances than Krohne EMF when connected with EMF sensor of Yokogawa. The developed system has similar performances with Krohne EMF when connected with EMF sensor of Shanghai Yinuo Instrument Co., Ltd.