Ultrasonic Flow Meter Discrete Cross-Correlation Processing
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Solution Overview
Problem
Existing ultrasonic fluid velocity measurement techniques face challenges in achieving accurate measurement of differential propagation times, especially at low flow rates, due to high measurement uncertainty and the need for precise subtraction of propagation times, which requires extraordinary accuracy and consumes excessive processing power.
Innovation Solution
The method employs discrete cross-correlation to estimate differential propagation time by reducing the number of cross-correlation values needed, using an expected differential propagation time to determine an initial discrete time shift, and applying interpolation to improve accuracy, while minimizing processing requirements and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If discrete cross-correlation is used to estimate differential propagation time, then measurement precision is improved, but processing power requirements increase
Solution Approach 1:
The patent segments the cross-correlation computation by dividing the signal into smaller processing blocks and performing correlation operations on segments rather than entire signals. This reduces the computational complexity from O(N²) to O(N×M) where M is the segment size, thereby reducing processing power requirements while maintaining measurement precision through overlapping segment analysis.
Solution Approach 2:
The patent applies partial action by computing cross-correlation only over a reduced search range around an estimated optimal lag value, rather than computing the full cross-correlation function across all possible lags. This partial computation approach achieves sufficient measurement precision for differential propagation time while significantly reducing the number of operations required.
2Productivity
If the number of cross-correlation values is reduced, then processing requirements are minimized, but measurement accuracy may deteriorate
Solution Approach 1:
The patent performs preliminary action by first computing a coarse cross-correlation to identify an approximate optimal lag range, then performing a refined cross-correlation computation only within this narrowed range. This two-stage approach reduces the number of full cross-correlation values needed while maintaining measurement accuracy, as the refined computation focuses resources on the critical region containing the true differential propagation time.
Solution Approach 2:
The patent substitutes direct mechanical computation of all cross-correlation values with an algorithmic approach using the Wiener-Khinchin theorem, which relates autocorrelation to the power spectral density. By transforming signals to the frequency domain, computing spectral densities, and then transforming back, the system achieves equivalent correlation results with reduced computational operations, improving processing efficiency without sacrificing accuracy.
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 significantly reduces measurement uncertainty and extends the range of flow rates that can be measured accurately, from approximately 16 liters per minute to beyond 40 liters per minute, while minimizing power consumption and processing demands.
Implementation Method 1
two ultrasonic transducers UT1 and UT2 are mounted inside a pipe 100
Implementation Method 2
let t12 be the propagation time (also known as time-of-flight) for an ultrasonic signal from ultrasonic transducer UT1 to ultrasonic transducer UT2
Implementation Method 3
Flowing fluid in the pipe will cause the down-stream propagation time to be slightly different than the up-stream propagation time
Data Source
AI summary
A flow meter ultrasonically measures fluid velocity in a pipe. Ultrasonic signals received by ultrasonic transducers are digitized. The difference between two ultrasonic propagation times is determined by computing a discrete cross-correlation of the digitized received signals. Computation time is reduced by computing only a few cross-correlation values near a peak cross-correlation value.