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Evaluating Targeting Accuracy in the Focal Plane for an Ultrasound-guided High-intensity Focused Ultrasound Phased-array System
Published on: March 6, 2019
Analysis of order-statistic CFAR threshold estimators for improved ultrasonic flaw detection
Summary
Optimal bandpass filtering enhances flaw detection in ultrasonic testing by analyzing spectral data. This method, using order-statistic processors, robustly identifies flaws even with interfering grain scatterers.
Area of Science:
- Ultrasonic testing
- Non-destructive evaluation
- Signal processing
Background:
- Flaw detection in pulse-echo ultrasonic testing is challenged by grain scatterers.
- Optimal bandpass filtering can improve signal-to-noise ratio for flaw echoes.
Purpose of the Study:
- To improve flaw detection in ultrasonic testing using optimal bandpass filtering.
- To develop robust adaptive thresholding techniques for flaw echo discrimination.
Main Methods:
- Optimal bandpass filtering based on spectral analysis of flaw and grain echoes.
- Adaptive thresholding using order-statistic (OS) processors: ranked and trimmed mean (TM).
- Analytical design of OS processors based on constant false-alarm rate (CFAR) detection.
Main Results:
- Optimal bandpass filtering effectively resolves flaw echoes obscured by grain scatterers.
- OS-CFAR and TM-CFAR processors demonstrate robust flaw echo detection.
- Achieved a constant false-alarm rate (CFAR) of 10^-4 even with outliers in threshold estimation range cells.
Conclusions:
- Optimal bandpass filtering combined with OS-CFAR processors significantly enhances flaw detection capabilities.
- The proposed methods provide robust and reliable flaw detection in challenging ultrasonic testing environments.
- This approach is effective for discriminating flaw echoes in the presence of significant grain noise.
