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Evaluation of an Extended Autocorrelation Phase Estimator for Ultrasonic Velocity Profiles Using Nondestructive
César Yutaka Ofuchi1, Fabio Rizental Coutinho2, Flávio Neves3
1Graduate School of Electrical Engineering and Computer Science (CPGEI), Federal University of Technology-Paraná (UTFPR), Avenida 7 de Setembro 3165, Curitiba 80230-901, Paraná, Brazil. ofuchi@utfpr.edu.br.
Sensors (Basel, Switzerland)
|August 13, 2016
Summary
The extended autocorrelation method (EAM) accurately measures fluid velocities beyond the Nyquist limit using ultrasonic devices, offering a computationally efficient alternative to traditional methods.
Area of Science:
- Fluid dynamics
- Ultrasonic measurement techniques
- Signal processing
Background:
- Autocorrelation method (ACM) is widely used for ultrasonic velocity profiling but limited by phase aliasing at higher velocities.
- Cross-correlation method (CCM) overcomes phase aliasing but requires significant computational resources.
- Extended autocorrelation method (EAM) is a recent technique combining ACM and CCM advantages.
Purpose of the Study:
- Evaluate and compare ACM, CCM, and EAM for ultrasonic velocity estimation.
- Assess performance below and beyond the Nyquist limit.
- Investigate EAM's computational efficiency and accuracy.
Main Methods:
- Comparison of three velocity estimators: ACM, CCM, and EAM.
- Utilized a nondestructive ultrasonic device on a controlled rotating cylinder flow.
- Evaluated performance using root-mean-square deviation variation coefficient (CVRMSD).
Main Results:
- EAM accurately measures velocities below the Nyquist limit with <2% CVRMSD.
- EAM and CCM effectively measure velocities beyond the Nyquist limit.
- EAM is computationally 15 times faster than CCM.
Conclusions:
- EAM provides accurate and efficient ultrasonic velocity measurements beyond the Nyquist limit.
- The study validates EAM for NDT applications, overcoming ACM limitations.
- Velocities up to six times the Nyquist limit are measurable with EAM and CCM under specific parameters.

