Fluid vibration type effusion meter self-adapting FFT power spectrum analysis and signal processing method

Abstract

The invention discloses a self-adapting FFT power spectrum analytical signal processing method of a vibrating type fluid flowmeter. A signal processing module is arranged between a primary transducer of a flowmeter and a secondary instrument of the flowmeter; an output signal S1 of the primary transducer with noise is input the signal processing module and goes through the FFT power spectrum analytical signal processing by the signal processing module, an effective vibratory impulse signal S3 without noise is output and provided for the secondary instrument of the flowmeter for the flow calculation so as to improve the noise proof property of the flowmeter and reduce the lower limit of the metering. The method of the invention avoids the pace losing and false triggering phenomena of the traditional analog signal processing, overcomes the shortcoming that the traditional single sampling frequency FFT power spectrum analytical method can not be adapted to the high and low frequency metering, searches for the sampling frequency in the manner of self-adaptation, improves the frequency resolution at low frequency, improves the metering precision of the flowmeter, reduces the low limit of the metering, is suitable for the vibrating type fluid flowmeter, particularly to the vibrating type fluid flowmeter powered by batteries.

Description

technical field [0001] The invention relates to a signal processing method applied to a fluid vibration flowmeter, in particular to a signal processing method for a fluid vibration flowmeter adaptive FFT power spectrum analysis. Background technique [0002] The fluid vibration flowmeter uses a specific structure to induce vibration when the fluid flows through its primary sensor, and determines the fluid velocity or flow through the secondary instrument to detect the vibration frequency. At present, fluid vibration flowmeters are widely used, but the measurement principle determines that its measurement is easily disturbed by external noise, especially when the flow rate is small and the vibration frequency is low, the noise leads to a poor signal-to-noise ratio of the output signal of the primary sensor, making it difficult to detect effective vibration signals , affecting metering performance. Therefore, it is extremely important for fluid vibrating flowmeters to find a ...

AI Technical Summary

Problems solved by technology

However, the existing FFT power spectrum analysis methods all use a single sampling frequency. Since the signal frequency is unknown, the sampling frequency is generally set to twice the maximum flow rate corresponding to the signal frequency value according to Shannon's theorem.

At the same time, in order to meet the battery-powered requirements of the flowmeter, it is necessary to use a low-power single-chip microcomputer for FFT power spectrum analysis instead of a DSP with high power consumption. The limited storage space of the single-chip microcomputer limits the number of sampling points

Therefore, although the existing digital signal processing method effectively solves the anti-noise problem and improves the repeatability of the flowmeter, but limited by the limited storage space of the single-chip microcomputer, the larger sampling frequency and lower number of sampling points at low flow rates will make the frequency resolution The rate cannot meet the requirements, which causes measurement errors, resulting in unsatisfactory performance of the flowmeter for small flow measurement

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