Research On Signal Modeling,Signal Processing And System For Flow Sensors

This thesis consists of three sections: non-linear dynamic modeling of the hot-film mass air flow sensor, signal modeling and processing of the electromagnetic flow sensor under sinusoidal excitation, and method study and system development of vortex flow sensor.(1) The nonlinear dynamic models and identification methods of sensor are studied aiming at the nonlinear dynamic characteristic of the hot-film mass air flow sensor. The block-oriented models are adopted to describe the nonlinear dynamic characteristics. The Vandermonde decomposition based identification method is studied, and a two-stage identification method is proposed to determine the model parameters. The simulation results show that two methods are effective, and the noise-rejecting ability of two-stage method is stronger.(2) Based on the static calibration experiments and dynamic experiments, the two-step identification method is adopted to build the uniform nonlinear dynamic Hammerstein model of the hot-film MAF sensor, which can describe the large/small flow-rate and positive/negative step responses. The performance indexes are calculated by the model step responses.(3) The operating principle of the electromagnetic flow sensor is analyzed, and its signal model is proposed to express the actions of both "transformer effect" and "eddy current" on the sensor. A two-step fitting method is proposed to identify the parameters of signal model according to the experimental data. The signal model can describe the relationship among the sensor output, flow-rate and exciting signal quantitatively.(4) The reference signal of the quadrature demodulation is adjusted according to the phase information of signal model of electromagnetic flow sensor proposed by ourselves. The quadrature interference is removed effectively, and the zero offset is decreased greatly.(5) In order to obtain better frequency characteristic, Butterworth wavelet filter banks are derived using the construction of finite impulse response (IIR) according to the wavelet perfect reconstruction condition. The problem of implementation of IIR wavelet filter banks is solved, and IIR wavelet filter banks are applied to the vortex signal with noise to extract the fundamental wave and measure its frequency. In frequency measurements a judgment method for wrong maximum value points is proposed and the fundamental frequency of signal is estimated by the least squares method, which decreases the influence of low frequency noises. An interpolation method in the parabola form is used to eliminate the error of non-integral cycle sampling.(6) The spectrum analysis is combined with the digital filtering to process the signal of the vortex flow sensor in order to eliminate the noise influence, e.g. effect of pipeline vibration on sensor. RFFT is adopted to perform the signal spectrum analysis to reduce the computation operations greatly. Thus the algorithm is easy to be realized in real time. The spectrum correction method is employed in the estimation of the vortex frequency to improve the measurement accuracy.(7) The digital signal process system of the vortex flowmeter is developed with the DSP chip of TMS320LF2407A as its processor. Limited amplitude filter is used to solve the problem of adjusting hardware circuitry parameters for large amplitude variation of sensor signal. In order to improve the measurement accuracy, the resolution of frequency is determined suitably, the spectrum correction method is adopted, and the compensation of temperature and pressure are performed. The software method is utilized to produce the output pulses with the timer of DSP to ensure their precision. Using data buffer of DSP, both signal sampling and calculation are performed at the same time to realize the signal processing in real time. The developed system is smaller, its cost is cheaper, and it almost has all required functions. The system can be used for vortex flowmeter with different sizes. The turn down ratio of the flowmeter is extended, and the ability of the noise -rejecting is enhanced.(8) The debugging, temperature and calibration experiments are conducted to verify the measurement accuracy, stability and reliability of the system. The system has been applied to the industrial fields.