Improvement of Ultrasonic Image by a Combination of Correlation-based Image Processing and Virtual Sources Applied to Non-destructive Evaluation

Ultrasonic signals are widely used to detect defects and characterize materials. In this field, the Total Focusing Method (TFM) imaging approach is commonly applied to post-process the ultrasonic data acquired by the Full Matrix Capture (FMC) of an array of ultrasonic transducers. Although the traditional FMC-TFM technique is considered as a reference standard, the energy transmitted in the material is limited by the use of a single transmitting element of the array and hence may provide a poor signal-to-noise ratio of the reconstructed image. To overcome this limitation and improve the image quality of highly noisy materials, this paper combines two noise-reduction methods, namely a modified Spatially Averaged Sub-Aperture Correlation Imaging and virtual sources. In the former, we further propose a modification in order to avoid the manual fine-tuning of a parameter presented in the original approach. The second consists of using several transmitting elements to increase the energy transmitted in the medium. Results showed that this combination was able to increase in 39 dB the signal-to-noise ratio. This result is 4.2 dB above the sum of individual gains of each technique which indicates a synergistic effect on increasing the image quality. Moreover, the use of virtual sources was capable of improving the reconstructed image where initially it is not possible to distinguish the noise from the desired signal. The application of the correlation approach in this scenario increased the quality of the reconstructed image significantly. The proposed combination was validated in a finite element model of a steel block with side-drilled holes used to mimic internal flaws in the material. Several noise levels were added to the numerically simulated signals in order to evaluate the performance of the proposed approach.