Least-squares estimation of imaging parameters for an ultrasonic array using known geometric image features

Area of Science:

• Non-destructive Testing and Evaluation
• Ultrasonic Imaging
• Signal Processing

Background:

• Ultrasonic array imaging is sensitive to errors in imaging parameters, degrading defect detection and characterization.
• Accurate imaging parameters are crucial for reliable non-destructive testing (NDT) and evaluation (NDE).

Purpose of the Study:

• To develop and validate an autofocus algorithm for estimating and correcting imaging parameter errors in ultrasonic array imaging.
• To enhance the performance of NDT/NDE by improving the quality of ultrasonic images.

Main Methods:

• An autofocus algorithm is presented that uses collected echo data and a priori image geometry knowledge.
• Focusing is achieved by isolating a known geometric feature and minimizing errors between data and a feature model.
• The algorithm estimates unknown parameters, specifically element positions in a flexible array coupled to a specimen with an unknown surface profile.

Main Results:

• Experimental results using a prototype flexible array demonstrate the algorithm's effectiveness.
• The autofocus algorithm successfully corrects imaging parameter errors, leading to improved image quality.
• Autofocused images are comparable in quality to benchmark images obtained with known imaging parameters.

Conclusions:

• The developed autofocus algorithm effectively corrects imaging parameter errors in ultrasonic array imaging.
• This method significantly enhances image quality for non-destructive testing applications.
• The algorithm shows promise for improving defect detection and characterization in real-world NDT scenarios.