Ke's mass flowmeter digital signal processing system based on AFF and SGA

Abstract

The invention discloses a Kose quality flowmeter digital signal processing system based on AFF and SGA comprising signal conditioning circuit, A / D converter, digital signal processor (DSP), liquid crystal display (LCD) circuit, keyboard input circuit, digital / analog (D / A) converter, power amplifying circuit and software. The method uses multi-to-one filtration, adaptive funnel type filtration (AFF) and Sliding Goertzel Algorithm for sampled data processing, by calculating the fundamental frequency and phase of the flow tube vibration, the time difference between the frequency and two-way signal can be obtained from the phase differential, thus acquiring the mass flow value and the density value, an actuating signal is produced by the frequency value from the DSP calculation and sent to D / A for power magnification, making the flow tube vibrate.

Description

technical field [0001] The present invention relates to a method and device for determining the fundamental frequency and phase difference of a Coriolis (abbreviated as Coriolis) mass flow sensor, especially with a digital signal processor (Digital Signal Processor, abbreviated as DSP) as the core, using Adaptive Funnel Shaped Filter (AFF for short) to adaptively enhance the signal linearly, track and measure the frequency of the signal; use the Sliding Goertzel Algorithm (Sliding Goertzel Algorithm, SGA for short) to measure the phase of the two signals Difference. Background technique [0002] The Coriolis mass flowmeter (hereinafter referred to as the Coriolis mass flowmeter) can directly measure the mass flow rate. It is one of the most rapidly developing flowmeters and has broad application prospects. A Coriolis mass flow meter requires its signal processing circuitry to accurately measure the phase difference of the signals from the two flow sensors and track changes ...

AI Technical Summary

Problems solved by technology

[0005] The problem that this kind of method exists is: (a) real-time performance is poor

The problem with this method is: the phase difference of the two sensor signals is very small (generally less than 4 degrees), so the amplitude of the differential amplifier is very small, and it is very susceptible to noise interference; the compensation method takes too much time, because the calculation of the phase difference once Need to collect 6 signals

In the first embodiment, two parameters are estimated, increasing the complexity of the algorithm

In the second embodiment, two cascaded ANFs are used, and the complexity of the algorithm is higher than that of the first embodiment; moreover, since the second-level ANF is based on the first-level ANF, only the first The second stage will converge after the first stage converges. Therefore, in the case of large frequency changes, the convergence speed will decrease instead.

In addition, the Goertzel algorithm used to calculate the phase difference may overflow when implemented with a fixed point (see J.A.Beraldin and W.Steenaart, "Overflow analysis of a fixed-point implementation of the Goertzel algorithm, IEEE Trans. Circuits and Systems, Vol.36 , No.2, February1989, pp.322-324)

Images