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Model-based reconstruction of ultrasonic array
data
S. Chatillon, E. Iakovleva, F. Reverdy, P. Calmon
and S.Mahaut CEA-LIST, Saclay
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Outline

• Context UT array simulation in CIVA
• Reconstruction algorithms

• Ray-model based imaging ( True  images)
•  FTP  algorithm (synthetic focusing,)
• Processing of the Full transfert matrix (MUSIC)

• Examples of applications
• Conclusions, perspectives

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Context UT array simulation in CIVA
Availability in CIVA of reliable, quantitative
and performant direct models for UT array

• Beam computations
• Simulation of flaw responses
• Computation of delay laws, ray calculations
• In complex geometries (CAD), anisotropic and
  heterogeneous materials

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Context UT array simulation in CIVA

• Application to a wide range of arrays

Example of 3D electronic scanning on a matrix
array
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Context New techniques of Data Acquisition

• Full Matrix Capture

• Programmation of (sophisticated) operating modes

• Electronic scanning (2D on linear array or 3D on
  matrix)
• 3D sectorial scannings
• transmit receive independant functions
• Per channel acquisitions modes

Ability into CIVA to take into account and to
simulate these features, and to simulate the
different techniques of data reconstruction.
Study of reconstruction algorithms
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Top view
Focusing (close to backwall) and beam steering in
three different planes
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Top view
Focusing (close to backwall) and beam steering in
three different planes
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Top view
Focusing (close to backwall) and beam steering in
three different planes
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Array data reconstruction in CIVA
Implementation in CIVA of reconstruction
algorithms exploiting the forwards models of CIVA

•  Corrected  images

• Application limited to classical beam-formed
  operating modes (T R, mechanical or electronic
  scanning)
• Principle The received signals are displayed
  along rays

•  FTP  algorithm

• Application to In principle any set of UT
  signals. Well-adapted to per channel acquisitions
• Principle Synthetic focusing as post-processing.

•  MUSIC  algorithm

• Application limited to FMC acquisitions
• Principle Processing of the full transfert
  matrix of the array

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FTP algorithm

• Objective To image a region of interest
  inspected with an array
• In principle applicable to any set of US signals
  (mechanical or electronic scanning, etc)
• Principle Coherent summation of the received
  signals for all the points of the Region of
  Interest.
• From modelling Theoretical times of flight of
  echoes corresponding to every shot and
  possible location of a scatterrer
• The use of the forwards models implemented in
  CIVA enables to deal with complex configurations

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Synthetic focusing Principle

Reconstruction
Times of flights
Amplitudes
TnP
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Synthetic focusing Principle

Reconstruction
Times of flights
Amplitudes
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Synthetic focusing Principle

Reconstruction
Times of flights
Amplitudes
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Examples of results

Steel block with planar irregular surface
containing two sets of Ø2mm side drilled holes
Linear array
Side drilled Holes
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Application to Full Matrix Capture acquisitions

On the same irregular part
Receiving element (n)

• Linear array 64 elements, 2MHz
• One shot One transmitting element
  All elements receiving
• 64 shots
• 64x64 received signals

Shot n1
Time
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Application to Full Matrix Capture acquisitions
Reconstruction through the planar surface

 Total Focusing 
Very good localization accuracy even in this
decentered probe position
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Application to Full Matrix Capture acquisitions
Reconstruction through the complex surface

 Total Focusing 
Again a very good localization accuracy
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Examples of experimental/ Simulated results
Reconstruction through a planar surface
Linear probe, 128 elements, 3.5 MHz

• FMC acquisition (M2M system)

• One shot One transmitting element
  All elements receiving
• 128 shots
• 128x128 received signals

elements
Detection of all the defects, even those
shadowed by other defect embedded at lower depth.
Side drilled holes Ø 1.5 mm
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Examples of experimental/ Simulated results

•  Full Matrix capture  Acquisition System
  (M2M) with a 2D matrix array

Matrix probe 11x11 éléments, 1 MHz

• Firing on the first element
• Reception on all the element
• Then acquisition on the next element
• Data Storage of the data

200 mm
Flat Bottomed Holes Ø 2 mm
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Examples of experimental/ Simulated results

• Reconstruction after focusing at each point

• Define a plane for the reconstruction
• Computation of arrival time and amplitude for
  each receiver
• Summation of the experimental amplitudes at
  these times
• Mapping of all the defects whithout mechanical
  scanning

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Examples of experimental/ Simulated results

• Simulation (CIVA 9.1a) and 3D reconstruction

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Performance Evaluation by simulation
Study of the influence of unaccuracy on probe
position over the reconstruction
FMC Simulation Linear array 64 elements, 2MHz
FTP processing with DX on probe position and
misorientation (tilt)
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Performance Evaluation by simulation
Influence of unaccuracy on probe position
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Performance Evaluation by simulation
Influence of unaccuracy on the surface description
FMC Simulation Linear array 64 elements, 2MHz
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Performance Evaluation by simulation
Influence of unaccuracy on the surface description
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Performance Evaluation by simulation
Influence of unaccuracy on the surface description
With discretized profiles
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Performance Evaluation by simulation
Influence of unaccuracy on the surface description
Effect of discretization (linear interpolation)
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Reconstruction in heterogeneous and anisotropic
part
Weld described as a set of homogeneous regions
made of the same anisotropic medium
differentiated by local crystal orientation .
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Reconstruction in heterogeneous and anisotropic
part
Evaluation by simulation of the influence of the
weld description
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Conclusion

• The new capacities of UT array systems offer new
  ways to improve Inspections methods
• A lot of Reconstruction algorithms are available
• CIVA can be used to evaluate these different
  algorithms within geometry, material, noise with
  synthetic simulated data and/or experimental data

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Perspective

• Through the project CIVA 2012, several
  universities will be able to integrate into CIVA
  their own development
• In a very next future the CIVA Platform will
  allow to the CIVA users to compare and to
  evaluate the reconstruction algorithms coming
  from different sources.