Comparative study of infrared thermography, ultrasonic C-scan, X-ray computed tomography and terahertz imaging on composite materials

L’évaluation non destructive (NDT) des matériaux composites est compliquée en raison de la vaste gamme de défauts rencontrés (y compris délaminage, microfissuration, fracture de la fibre, retrait des fibres, fissuration matricielle, inclusions, vides et dommages aux chocs). La capacité de caractériser quantitativement le type, la géométrie et l’orientation des défauts est essentielle. La thermographie infrarouge (IRT), en tant que technique de diagnostic d’image, peut satisfaire le besoin industriel croissant de NDT&E. Dans la thèse, la thermographie par excitation optique et mécanique a été utilisée pour étudier différents matériaux composites, dont 1) des préformes sèches en fibres de carbone, 2) des composites de fibres naturelles, 3) des composites hybrides de basalte-fibres de carbone soumis à une charge d’impact (séquence de type sandwich et séquence d’empilement intercalé), 4) des défauts micro-dimensionnés dans un composite polymère renforcé de fibre de carbone (CFRP) en 3D avec une couture de type « joint en T », et 5) des peintures sur toile qui peuvent être considérées comme des matériaux composites. Une nouvelle technique IRT de thermographie de ligne par micro-laser (micro-LLT) a été proposée pour l’évaluation des porosités submillimétriques dans le CFRP. La microscopie de points par micro-laser (micro-LST) et la micro-vibrothermographie (micro-VT) ont également été présentées avec l’utilisation de microlentilles. La thermographie pulsée (PT) et la thermographie modulée « à verrouillage » (LT) ont été comparées à la tomographie par rayons X (TC) pour validation. Le C-scan ultrasonore (UT) et l’imagerie par ondes tera-hertziennes en onde continue (CW THz) ont également été réalisés à des fins comparatives. L’inspection par techniques thermographiques est une question ouverte à discuter pour le public scientifique. En fait, la thermographie par impulsions (PPT) basée sur la transformation de phase a été utilisée pour estimer la profondeur des dommages. Pour traiter les données thermographiques, on a également utilisé la reconstruction de signal thermographique de base (B-TSR), la thermographie des composants principaux (PCT) et la thermographie des moindres carrés partiels (PLST). Enfin, une analyse complète et comparative basée sur le diagnostic d’images thermographiques a été menée en vue d’applications industrielles potentielles.Non-destructive testing (NDT) of composite materials is complicated due to the wide range off laws encountered (including delamination, micro-cracking, fiber fracture, fiber pullout, matrix cracking, inclusions, voids, and impact damage). The ability to quantitatively characterize the type, geometry, and orientation of flaws is essential. Infrared thermography (IRT), as an image diagnostic technique, can satisfy the increasing industrial need for NDT&E. In the thesis, optical and mechanical excitation thermography were used to investigate different composite materials, including 1) carbon fiber dry preforms, 2) natural fiber composites, 3) basalt-carbon fiber hybrid composites subjected to impact loading (sandwich-like and intercalated stacking sequence), 4) micro-sized flaws in a stitched T-joint 3D carbon fiber reinforced polymer composite (CFRP), and 5) paintings on canvas which can be considered as composite materials. Of particular interest, a new IRT technique micro-laser line thermography (micro-LLT) was proposed for the evaluation of submillimeter porosities in CFRP. Micro-laser spot thermography (micro-LST) and micro-vibrothermography (micro-VT) were also presented with the usage of a micro-lens. Pulsed thermography (PT) and lock-in thermography (LT) were compared with x-ray computed tomography (CT) for validation. Ultrasonic C-scan (UT) and continuous wave terahertz imaging (CW THz) were also conducted for the comparative purpose. The inspection by thermographic techniques is an open matter to be discussed for the scientific audience. In fact, pulse phase thermography (PPT) based on phase transform was used to estimate the damage depth. Basic thermographic signal reconstruction (B-TSR), principal component thermography (PCT) and partial least squares thermography (PLST) (another more recent advanced image processing technique) were also used to pro-cess the thermographic data. Finally, a comprehensive and comparative analysis based on thermographic image diagnostics was conducted in view of potential industrial applications

Compressed Sensing for Open-ended Waveguide Non-Destructive Testing and Evaluation

Ph. D. ThesisNon-destructive testing and evaluation (NDT&E) systems using open-ended waveguide (OEW) suffer from critical challenges. In the sensing stage, data acquisition is time-consuming by raster scan, which is difficult for on-line detection. Sensing stage also disregards demand for the latter feature extraction process, leading to an excessive amount of data and processing overhead for feature extraction. In the feature extraction stage, efficient and robust defect region segmentation in the obtained image is challenging for a complex image background. Compressed sensing (CS) demonstrates impressive data compression ability in various applications using sparse models. How to develop CS models in OEW NDT&E that jointly consider sensing & processing for fast data acquisition, data compression, efficient and robust feature extraction is remaining challenges. This thesis develops integrated sensing-processing CS models to address the drawbacks in OEW NDT systems and carries out their case studies in low-energy impact damage detection for carbon fibre reinforced plastics (CFRP) materials. The major contributions are: (1) For the challenge of fast data acquisition, an online CS model is developed to offer faster data acquisition and reduce data amount without any hardware modification. The images obtained with OEW are usually smooth which can be sparsely represented with discrete cosine transform (DCT) basis. Based on this information, a customised 0/1 Bernoulli matrix for CS measurement is designed for downsampling. The full data is reconstructed with orthogonal matching pursuit algorithm using the downsampling data, DCT basis, and the customised 0/1 Bernoulli matrix. It is hard to determine the sampling pixel numbers for sparse reconstruction when lacking training data, to address this issue, an accumulated sampling and recovery process is developed in this CS model. The defect region can be extracted with the proposed histogram threshold edge detection (HTED) algorithm after each recovery, which forms an online process. A case study in impact damage detection on CFRP materials is carried out for validation. The results show that the data acquisition time is reduced by one order of magnitude while maintaining equivalent image quality and defect region as raster scan. (2) For the challenge of efficient data compression that considers the later feature extraction, a feature-supervised CS data acquisition method is proposed and evaluated. It reserves interested features while reducing the data amount. The frequencies which reveal the feature only occupy a small part of the frequency band, this method finds these sparse frequency range firstly to supervise the later sampling process. Subsequently, based on joint sparsity of neighbour frame and the extracted frequency band, an aligned spatial-spectrum sampling scheme is proposed. The scheme only samples interested frequency range for required features by using a customised 0/1 Bernoulli measurement matrix. The interested spectral-spatial data are reconstructed jointly, which has much faster speed than frame-by-frame methods. The proposed feature-supervised CS data acquisition is implemented and compared with raster scan and the traditional CS reconstruction in impact damage detection on CFRP materials. The results show that the data amount is reduced greatly without compromising feature quality, and the gain in reconstruction speed is improved linearly with the number of measurements. (3) Based on the above CS-based data acquisition methods, CS models are developed to directly detect defect from CS data rather than using the reconstructed full spatial data. This method is robust to texture background and more time-efficient that HTED algorithm. Firstly, based on the histogram is invariant to down-sampling using the customised 0/1 Bernoulli measurement matrix, a qualitative method which only gives binary judgement of defect is developed. High probability of detection and accuracy is achieved compared to other methods. Secondly, a new greedy algorithm of sparse orthogonal matching pursuit (spOMP)-based defect region segmentation method is developed to quantitatively extract the defect region, because the conventional sparse reconstruction algorithms cannot properly use the sparse character of correlation between the measurement matrix and CS data. The proposed algorithms are faster and more robust to interference than other algorithms.China Scholarship Counci

Novel Approaches for Nondestructive Testing and Evaluation

Nondestructive testing and evaluation (NDT&E) is one of the most important techniques for determining the quality and safety of materials, components, devices, and structures. NDT&E technologies include ultrasonic testing (UT), magnetic particle testing (MT), magnetic flux leakage testing (MFLT), eddy current testing (ECT), radiation testing (RT), penetrant testing (PT), and visual testing (VT), and these are widely used throughout the modern industry. However, some NDT processes, such as those for cleaning specimens and removing paint, cause environmental pollution and must only be considered in limited environments (time, space, and sensor selection). Thus, NDT&E is classified as a typical 3D (dirty, dangerous, and difficult) job. In addition, NDT operators judge the presence of damage based on experience and subjective judgment, so in some cases, a flaw may not be detected during the test. Therefore, to obtain clearer test results, a means for the operator to determine flaws more easily should be provided. In addition, the test results should be organized systemically in order to identify the cause of the abnormality in the test specimen and to identify the progress of the damage quantitatively