Coriolis Flowmeter Signal Processing Phase Measurement
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Solution Overview
Problem
Conventional Coriolis flowmeters face challenges in maintaining high measurement precision and speed when fluid temperature changes, air bubbles mix into the fluid, or when the fluid rapidly changes from a gas to a liquid, due to complex computation requirements and large memory consumption, leading to reduced measurement accuracy and high computational burdens.
Innovation Solution
A signal processing method that employs 1/N quadrature frequency conversion to reduce the input frequency band, allowing for stable phase measurement with high filtering performance using a reduced number of filter tables and simplified computing processes, even under varying conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional phase measurement methods with multiple filter tables are used, then measurement precision is maintained under varying fluid conditions, but computational processing amount and memory consumption increase significantly
Solution Approach 1:
The patent changes the parameter of filter frequency characteristics by dynamically adjusting filter coefficients based on detected vibration frequency, rather than using multiple fixed filter tables. This allows the filter to adapt to frequency variations caused by fluid condition changes while maintaining constant computational complexity and memory usage.
Solution Approach 2:
The patent implements dynamic filter adaptation where the filter characteristics automatically adjust to match the current vibration frequency of the flow tube. This dynamic approach replaces the static multiple-filter-tables method, enabling the system to handle varying fluid conditions (temperature, phase changes, air bubbles) without increasing computational burden.
2Measurement precision
If multiple filter tables are prepared for different frequency bands, then phase measurement accuracy is maintained under varying fluid conditions, but memory consumption increases
Solution Approach 1:
Instead of storing multiple filter tables in memory for different frequency bands, the patent uses a single adaptive filter whose coefficients are adjusted in real-time based on the detected vibration frequency. This parameter adaptation approach eliminates the need for large memory allocations while maintaining measurement accuracy across varying conditions.
3Measurement precision
If sampling rate is adjusted for different fluid conditions, then measurement accuracy is maintained, but device complexity and control complexity increase
Solution Approach 1:
The patent maintains a constant sampling rate while adjusting filter coefficients to adapt to changing fluid conditions. This approach avoids the complexity of dynamic sampling rate adjustment while still achieving accurate phase measurement under varying temperature, phase, and composition conditions through filter parameter adaptation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables constant precision measurements with high filtering performance and significantly reduces computational processing, maintaining accuracy and speed across changing fluid conditions without the need for complex filter table switching or sampling rate adjustments.
Implementation Method 1
A combination of a coil and a magnet are generally used as driving means for driving the flow tube
Implementation Method 2
a Coriolis force acting on a flow tube (hereinafter, flow tube to be vibrated is referred to as flow tube) is proportional to a mass flow rate
Data Source
AI summary
A signal processing method for a Coriolis flowmeter including: performing frequency conversion of a first digital signal, the frequency conversion performed on the first digital signal modulating the frequency of the first digital signal so that the frequency of the first digital signal after the frequency conversion is 1/Nth of the frequency of the first digital signal before the frequency conversion, where N is an integer; performing frequency conversion of a second digital signal, the frequency conversion performed on the second digital signal modulating the frequency of the second digital signal so that the frequency of the second digital signal after the frequency conversion is 1/Nth of the frequency of the second digital signal before the frequency conversion; and measuring a phase difference between (i) the frequency converted first digital signal and (ii) the frequency converted second digital signal.