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Title: Signal processing for next generation coriolis flow metering
Author: Li, Ming
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2018
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This thesis aims to develop new signal processing techniques for Coriolis flowmeters. Two/multi-phase flow metering is a long established problem in many applications (e.g. the oil & gas, chemical, biotech, pharmaceutical industries) and no perfect solution is available. In the light of this challenge, recent developments in the Coriolis flowmeters are explored and issues for applying Coriolis flowmeter in two-phase flow conditions are identified. Benchmarks for both empty-to-full batch and continuous two-phase flow reflecting real-world applications are developed for evaluating signal processing techniques. Then current Coriolis flowmeter signal processing techniques are reviewed and tested using the benchmark examples. A new family of signal processing techniques based on complex signal processing are developed: these include Complex Bandpass Filter (CBF), Complex Notch Filter (CNF) and a combination of CBF with CNF (CBF-CNF). The new techniques are compared with the current methods via the benchmarks and exhibit good performance. CBF and CBF-CNF are implemented in a prototype transmitter to test alongside with an 'Oxbox' transmitter which is a laboratory version of the Foxboro CFT-50/1 (a commercial transmitter developed by the Oxford research group). Signal generator tests are carried out first in order to validate the proper operation of each new technique. Next, single-phase flow tests are carried out to demonstrate that the new algorithms running on the prototype transmitter measure accurately and, joined to a flow tube, can perform as a basic Coriolis flowmeter. Finally, two-phase (water/air) flow tests are carried out with the new algorithms. The performance is compared with that of the Oxbox. From the results, the new CBF and CBF-CNF algorithms perform comparably with the Oxbox at low Gas Void Fraction (GVF), while at high GVF they reduce frequency and phase difference standard deviation by as much as 10 times. Finally, a new non-linear state space model with Extended Kalman Filter (EKF) is developed as a further promising signal processing technique for Coriolis flowmeter. The new model shows good performance compared with both existing and complex signal processing based techniques but some challenges need to be solved before EKF can be implemented in a prototype transmitter.
Supervisor: Henry, Manus ; Duncan, Stephen Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Coriolis Flow Meter ; Signal Processing