Model-Based Iterative Reconstruction for One-Sided Ultrasonic Nondestructive Evaluation

Almansouri, Hani; Venkatakrishnan, Singanallur; Bouman, Charles A.; Santos-Villalobos, Hector

doi:10.1109/tci.2018.2883218

Cited by 14 publications

(9 citation statements)

References 25 publications

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“…In this section, we introduce a model of the multi-layer acoustic propagation based on an extension of the singlelayer model used in [22]. Figure 2 illustrates the problem.…”

Section: A Multi-layer Acoustic Propagation Modelmentioning

confidence: 99%

“…In [15,21], the forward model is designed to handle plane-wave imaging. Recently, the MBIR approach of [22] used a propagation model of the ultrasound through the media and combined all the data from the source-detector pairs to jointly reconstruct a fully 3D image. However, current MBIR approaches have limitations when imaging through heterogeneous materials.…”

Section: Introductionmentioning

confidence: 99%

“…However, current MBIR approaches have limitations when imaging through heterogeneous materials. In a single-layer structure, the time delay can be easily computed using Snell's law [22,23]. However, in structures containing two layers, the time delay no longer has a closed form that can be easily computed using Snell's law [24].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Model-Based Reconstruction for Collimated Beam Ultrasound Systems

Alanazi

Venkatakrishnan

Santos-Villalobos

et al. 2022

ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…In this section, we introduce a model of the multi-layer acoustic propagation based on an extension of the singlelayer model used in [22]. Figure 2 illustrates the problem.…”

Section: A Multi-layer Acoustic Propagation Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Model-Based Reconstruction for Collimated Beam Ultrasound Systems

Alanazi

Venkatakrishnan

Santos-Villalobos

et al. 2022

ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…Pressure tubes are inspected using Ultrasonic Testing (UT), a non-destructive examination (NDE) technique, to assess fitness for service. The usage of NDE in the inspection of nuclear power plants has been previously discussed in [5][6][7][8][9][10]. CANDU TM reactors contain 380-480 fuel channels.…”

Section: Introductionmentioning

confidence: 99%

Using Deep Learning to Automate the Detection of Flaws in Nuclear Fuel Channel UT Scans

Hammad

Simpson²,

Hall³

2022

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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Nuclear reactor inspections are critical to ensure the safety and reliability of a nuclear facility's operation. In Canada, Ultrasonic Testing (UT) is used to inspect the health of pressure tubes which are part of Canada's Deuterium Uranium (CANDU™) reactor's fuel channels. Currently, analysis of UT scans is performed by manual visualization and measurement to locate, characterize, and disposition flaws. Therefore, there is motivation to develop an automated method that is fast and accurate. In this paper, a proof of concept (PoC) that automates the detection of flaws in nuclear fuel channel UT scans using a convolutional neural network (CNN) is presented. The CNN model was trained after constructing a dataset using historical UT scans and the corresponding inspection results. The requirement for this prototype was to identify the location of at least a portion of each flaw in UT scans while minimizing false positives (FPs). The proposed CNN model achieves this target by automatically identifying at least a portion of each flaw where further manual analysis is performed to identify the width, the length, and the type of the flaw.

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“…Fewer spatial and temporal grid points are needed for accurate simulations [51]. Recently many authors have used the k-Wave toolbox in applications related to attenuation in ultrasonic computed tomography [53], guided waves in layered structures [54] and [55] time domain, power law attenuation in breast and liver tissues [56], one-sided ultrasonic nondestructive evaluation [57], high intensity focused ultrasound [58], nonlinear ultrasound propagation in absorbing media [59], ultrasonic transducers field modelling [60], and 3-D ultrasound imaging [61].…”

Section: Introductionmentioning

confidence: 99%

Ultrasonic Scattering Attenuation in Nodular Cast Iron: Experimental and Simulation Studies

Santos

2021

SV-JME

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This work evaluates the ultrasonic scattering attenuation of structures with complex scatterer distributions via experimental and simulation studies. The proposed approach uses experimental attenuation knowledge to infer the scatterer size and its concentration in the studied structures, which are important for the effective construction of simulated models. The MATLAB k-Wave toolbox has been used to implement the simulator. Several cast-iron samples have been used to demonstrate the importance of simulation in the characterization of such structures. First, the scattering attenuation was evaluated using the Truell and Papadakis models, and then the results were compared with experimental ones. Emphasis was given to the Papadakis approach because it takes into account the scatterer size distribution. It is demonstrated that both analytical models provide results that are far from the experimental ones. The developed simulator for the studied samples led to a predictive model, in which the attenuation was proportional to the fifth power of the scatterer size, and the corresponding formulation is close to the one proposed by the analytical models.

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Model-Based Iterative Reconstruction for One-Sided Ultrasonic Nondestructive Evaluation

Cited by 14 publications

References 25 publications

Model-Based Reconstruction for Collimated Beam Ultrasound Systems

Model-Based Reconstruction for Collimated Beam Ultrasound Systems

Using Deep Learning to Automate the Detection of Flaws in Nuclear Fuel Channel UT Scans

Ultrasonic Scattering Attenuation in Nodular Cast Iron: Experimental and Simulation Studies

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