Ultrasonic Imaging based on Approximated Minimum Variance Beamforming and Its Application in Non-Destructive Test of Boiler Tubes

Ultrasonic phased array imaging has found wide applications in industrial non-destructive test (NDT) including defect and crack detection in industrial samples and weld inspection. In this paper, an approximated minimum variance based beamforming method is proposed to improve the defect detection accuracy and reducing the background noise in the phased array ultrasonic imaging. The proposed method is employed in the boiler tube NDT. The matrix inverse approximation is computed using matrix inverse lemma such that the beamforming is performed proportional to the received signal amplitude. The performance of the proposed method is quantitatively and qualitatively evaluated in both theoretical and practical tests and compared with similar beamforming techniques. It is shown that the proposed method is able to reduce the image background noise while keeping the defect detection ability in comparison to both delay-and-sum and adaptive minimum variance beamforming methods. It also leads to defect detection enhancement compared with the minimum variance method. The computational complexity of the proposed method is less than that of both conventional and adaptive minimum variance beamforming methods.