Time difference detection based on sliding window all-phase FFT and Kalman filtering for precise flow measurement.

Area of Science:

• Instrumentation and Measurement Science
• Fluid Dynamics and Control

Background:

• Coriolis mass flowmeters (CMF) are crucial for precise mass flow rate measurement.
• Traditional frequency domain methods for CMF face challenges with spectrum leakage, impacting accuracy.
• Existing methods require improvement in stability and response speed for industrial applications.

Purpose of the Study:

• To develop a novel time difference detection method for CMF to overcome spectrum leakage.
• To enhance the stability and response speed of CMF measurements.
• To validate the proposed methods for improved industrial applicability.

Main Methods:

• Implemented a new time difference detection technique using a sliding window and all-phase fast Fourier transform (FFT).
• Reduced computational complexity by accounting for signal frequency variations.
• Applied a Kalman filtering algorithm, incorporating variance detection, for advanced post-processing and signal stabilization.

Main Results:

• The proposed method effectively mitigates spectrum leakage in CMF.
• Achieved superior accuracy of better than 0.5‰ and repeatability of better than 0.2‰ for single-phase fluids.
• Demonstrated significant improvements in measurement stability and response speed.

Conclusions:

• The novel time difference detection and Kalman filtering methods significantly enhance CMF accuracy and performance.
• The validated system offers a robust solution for industrial mass flow measurement.
• This advancement supports broader and more reliable industrial applications of Coriolis mass flowmeters.