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ASME J Nondestructive Evaluation. 2018;1(3):031001-031001-19. doi:10.1115/1.4039359.

Composite materials find wide range of applications due to their high strength-to-weight ratio. Due to this increasing dependence on composite materials, there is a need to study their mechanical behavior in case of damage. There are several extended nondestructive testing (ENDT) and structural health-monitoring (SHM) methods for the assessment of the mechanical properties each with their set of advantages and disadvantages. This paper presents a comparative study of three distinct damage detection methods (infrared thermography (IRT), neutral axis (NA) method based on optical strain sensor measurements, and terahertz spectroscopy) for the detection of delamination and temperature-induced damage in a simple glass fiber reinforced polymer (GFRP) beamlike structure. The terahertz spectroscopy is a specialized technique suitable for detecting deterioration inside the structure but has limited application for in-service performance monitoring. Similarly, the IRT technique in the active domain may be used for in situ monitoring but not in in-service assessment. Both methods allow the visualization of the internal structure and hence allow identification of the type and the extent of damage. Fiber optic sensors (especially fiber Bragg grating (FBG)) due to their small diameter and no need of calibration can be permanently integrated within the sample and applied for continuous dynamic strain measurements. The measured strain is treated as an input for neutral axis (NA) method, which as a damage-sensitive feature may be used for in-service monitoring but gives absolutely no information about the type and extent of damage. The results for damage detection based on proposed comparative studies give a complete description of the analyzed structure.

Commentary by Dr. Valentin Fuster
ASME J Nondestructive Evaluation. 2018;1(3):031002-031002-9. doi:10.1115/1.4039691.

X-ray computed tomography (CT) is a powerful tool for industrial inspection. However, the harsh conditions encountered in some production environments make accurate motion control difficult, leading to motion artifacts in CT applications. A technique is demonstrated that removes motion artifacts by using an iterative-solver CT reconstruction method that includes a bulk Radon transform shifting step to align radiographic data before reconstruction. The paper uses log scanning in a sawmill as an example application. We show how for a known nominal object density distribution (circular prismatic in the case of a log), the geometric center and radius of the log may be approximated from its radiographs and any motion compensated for. This may then be fed into a previously developed iterative reconstruction CT scheme based on a polar voxel geometry and useful for describing logs. The method is validated by taking the known density distribution of a physical phantom and producing synthetic radiographs in which the axis of object rotation does not coincide with the center of field of view for a hypothetical scanner geometry. Reconstructions could then be made on radiographs that had been corrected and compared to those that had not. This was done for progressively larger offsets between these two axes and the reduction in voxel density vector error studied. For CT applications in industrial settings in which precise motion control is impractical or too costly, radiographic data shifting and scaling based on predictive models for the Radon transform appears to be a simple but effective technique.

Commentary by Dr. Valentin Fuster

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