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Autofocusing Array Imaging in Anisotropic Weld Structure (pp. 145-158) $100.00
Authors:  (Jie Zhang, Department of Mechanical Engineering, University Walk, University of Bristol, Bristol, United Kingdom)
The quality of an ultrasonic array image depends on accurate information about its
acoustic properties. Inaccuracy of acoustic properties can cause image degradation such
as blurring, mislocation of reflectors and the introduction of artefacts. In this chapter, for
the specific case of an inhomogeneous and anisotropic austenitic steel weld, Monte Carlo
Markov Chain (MCMC) inversion is used to estimate unknown acoustic properties from
array data. The approach uses active beacons that transmit ultrasound through the
anisotropic weld which is captured by a receiving array. A forward model of the
ultrasonic array data is then optimised with respect to the experimental data using a
MCMC inversion. The result of this process is the extraction of a material property map
that describes the anisotropy distribution within the weld region. These extracted material
properties are then used within an imaging algorithm, the Total Focusing Method, to
produce autofocused images. This MCMC inversion approach is first applied to
simulated data which is used to test the convergence, robustness and accuracy of the
method and its implementation. In this case the extracted weld map is used to show
improved imaging of defects within the weld as compared to an image formed assuming
a constant velocity. 

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Autofocusing Array Imaging in Anisotropic Weld Structure (pp. 145-158)