Skip to Main content Skip to Navigation
Journal articles

Ultrasonic imaging of defects in coarse-grained steels with the decomposition of the time reversal operator

Abstract : In the present work, the Synthetic Transmit Aperture (STA) imaging is combined with the Decomposition of the Time Reversal Operator (DORT) method to image a coarse grained austenitic-ferritic steel using a contact transducer array. The highly heterogeneous structure of this material produces a strong scattering noise in ultrasound images. Furthermore, the surface waves guided along the array interfere with the bulk waves backscattered by defects. In order to overcome these problems, the DORT method is applied before calculating images with the STA algorithm. The method consists in analyzing in the frequency domain the singular values and singular vectors of the full array transfer matrix. This paper first presents an analysis of the singular values of different waves contained in the data acquisition, which facilitates the identification of the subspace associated with the surface guided waves for filtering operations. Then, a filtered matrix is defined where the contribution of structural noise and guided waves are reduced. Finally, in the time domain, the STA algorithm is applied to this matrix in order to calculate an image with reduced structural noise. Experiments demonstrate that this filtering improves the signal-to-noise ratio by more than 12 dB in comparison with the STA image before filtering.
Document type :
Journal articles
Complete list of metadatas

https://hal-cea.archives-ouvertes.fr/cea-01845390
Contributor : Léna Le Roy <>
Submitted on : Friday, July 20, 2018 - 1:14:55 PM
Last modification on : Saturday, September 26, 2020 - 11:44:10 PM

Identifiers

Citation

E. Lopez Villaverde, S. Robert, C. Prada. Ultrasonic imaging of defects in coarse-grained steels with the decomposition of the time reversal operator. Journal of the Acoustical Society of America, Acoustical Society of America, 2016, 140 (1), pp.541-550. ⟨10.1121/1.4958683⟩. ⟨cea-01845390⟩

Share

Metrics

Record views

115