Terahertz (THz) imaging is increasingly used in the cultural heritage field. In particular, continuous wave (CW) and low frequency THz is

In this paper, optical and mechanical excitation thermography were used to investigate basalt fiber reinforced polymer (BFRP), carbon fiber reinforced polymer (CFRP) and basalt-carbon fiber hybrid specimens subjected to impact loading. Interestingly, two different hybrid structures including sandwichlike and intercalated stacking sequence were used. Pulsed phase thermography (PPT), principal component thermography (PCT) and partial least squares thermography (PLST) were used to process the thermographic data. X-ray computed tomography (CT) was used for validation. In addition, signal-to-noise ratio (SNR) analysis was used as a means of quantitatively comparing the thermographic results. Of particular interest, the depth information linked to Loadings in PLST was estimated for the first time. Finally, a reference was provided for taking advantage of different hybrids in view of special industrial applications.

Stitching is used to reduce incomplete infusion of T-joint core (dry-core) and reinforce T-joint structure. However, it might cause new types of flaws, especially micro-sized flaws. In this paper, a new micro-laser line thermography (micro-LLT) is presented. X-ray micro-computed tomography (micro-CT) was used to validate the infrared results. The micro-LLT and micro-CT inspection are compared. Then, a finite element analysis (FEA) is performed. The geometrical model needed for finite element discretization was developed from micro-CT measurements. The model is validated for the experimental results. Finally a comparison of the experiments and simulation is conducted. The infrared experimental phenomenon and results are explained based on the FEA results

Traditional pipeline magnetic flux leakage (MFL) internal technology mainly uses axial excitation method, which could not recognize the narrow crack defects in the axial direction of the pipe. In this paper, by using a linear magnetic dipole model to study the circumferential excitation method, the detection model of axial crack in pipeline is established, and the relationship between MFL signals and the geometry characteristics of axial cracks is calculated. Finally, the detection accuracy and identification method of axial cracks is analyzed. Research results show that: non-uniform magnetic field generated by circumferential excitation can effectively detect the narrow cracks in the axial direction of the pipeline and distinguish the depth and the width characteristics of cracks. However, the background magnetic fields near the magnetic poles have great influence on the detection accuracy, and the smooth interpolation method of the cubic-spline interpolation can be used to reduce the influence effectively. IntroductionPipeline MFL internal inspection technology is the mainstream technology to maintain the safe operation of long-distance oil -gas pipeline [1][2][3][4] . This technology belongs to the monopoly technology in the world, for it is only mastered by a few Highlights 1. The MFL internal inspection technology can maintain the safe operation of pipelines.2. The axial cracks are more hazardous than circumferential cracks for pipelines.3. The circumferential excitation method can improve the confidence of the MFL device. 4. The axial cracks can be identified by circumferential excitation method.5. The MFL internal inspection of defects in arbitrary direction is possible to realize.

Abstract. Stitching is used to reduce dry-core (incomplete infusion of T-joint core) and reinforce T-joint structure. However, it may cause new types of flaws, especially submillimeter flaws. In this paper, microscopic inspection, ultrasonic c-scan, pulsed thermography, vibrothermography and laser spot thermography are used to investigate the internal flaws in a stitched T-joint CFRP. Then, a new micro-laser line thermography is proposed. Micro-CT is used to validate the infrared results. A comparison between micro-laser line thermography and micro-CT is performed. As a conclusion, micro-laser line thermography can detect the internal submillimeter defects. However, the depth and the size of defects can affect the detection results. The micro-porosities with a diameter of less than 54 µm are not detected in the micro-laser line thermography results. Micro-laser line thermography can detect the micro-porosity (a diameter of 0.162 mm) from the depth of 90 µm. However, it cannot detect the internal micro-porosity (a diameter of 0.216 mm) from the depth of 0.18 mm. The potential causes are given. Finally a comparative study is conducted.

Fiber orientation in composite materials is an important feature since the arrangement or orientation of the fibers relative to one another has a significant influence on the strength and other properties of fiber reinforced composites.In this paper we present a method to assess the fiber orientation on the surface of carbon fiber reinforced polymer (CFRP) laminates. More specifically, a diode-laser beam is used to locally heat a small spot on the surface of the sample. Observation of the heat pattern in the infrared spectrum enables the assessment of the fiber orientation. Different samples and different regions on the surface of the samples are tested in order to estimate the precision of the method.

Advanced materials such as continuous carbon fiber-reinforced thermoplastic (CFRP) laminates are commonly used in many industries, mainly because of their strength, stiffness to weight ratio, toughness, weldability, and repairability. Structural components working in harsh environments such as satellites are permanently exposed to some sort of damage during their lifetimes. To detect and characterize these damages, non-destructive testing and evaluation techniques are essential tools, especially for composite materials. In this study, artificial intelligence was applied in combination with infrared thermography to detected and segment impact damage on curved laminates that were previously submitted to a severe thermal stress cycles and subsequent ballistic impacts. Segmentation was performed on both mid-wave and long-wave infrared sequences obtained simultaneously during pulsed thermography experiments by means of a deep neural network. A deep neural network was trained for each wavelength. Both networks generated satisfactory results. The model trained with mid-wave images achieved an F1-score of 92.74% and the model trained with long-wave images achieved an F1-score of 87.39%.

In this paper, an infrared thermography technique is used to assess the fiber orientation on the surface of carbon fiber-reinforced polymer (CFRP) moulded with randomly-oriented strands (ROS). Due to the randomness of the material a point by point inspection would be very time consuming. In this paper it is propose the use a flying laser spot technique to heat a line-region on the surface of the sample instead of a spot. During our experiments, a flying laser spot inspection was performed in a half of a minute while a point by point inspection of the same area would last about 25 minutes. Artificial neural network (ANN) is then used to estimate the fiber orientation over the heated line. The classification rate obtained with the network was 91.2% for the training stage and 71.6% for the testing stage.