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The characterization of micro cracks on metal surface plays an important role in the process of manufacturing and using, which has attracted a lot of attention. This is mainly due to the fact that the size of defects is smaller and the depth of defects is difficult to predict compared with metal materials with larger plane, which is still challenging. In order to solve this problem, this paper proposes a characterization method of surface defects based on reflective laser thermography, and designs a laser heating nondestructive testing system based on reflection. The system includes a semiconductor laser to heat the surface of metal cracks, and an infrared imager to record changes in the temperature field of the metal surface. In the process of data analysis, an Otsu adaptive threshold segmentation method is selected to quantify the defect size, which can control the quantification accuracy of defect size within 25%. A derivative analysis method is proposed to quantify the depth of defects, which can control the depth quantification accuracy of tiny defects within 7%.

The applicability of active thermography as a non-destructive method to distinguish heat treated from not-treated boron steel has been investigated. While the usual hardness semi-destructive tests influence the inspected surface, laser thermography is capable of verifying the effectiveness of heat treatment in boron steel in a non-destructive way without any surface modification. The procedure has been verified on two plates of boron steels with different structures (100% ferritic–pearlitic and 100% martensitic).

Spot welding is a crucial process step in various industries. However, classification of spot welding quality is still a tedious process due to the complexity and sensitivity of the test material, which drain conventional approaches to its limits. In this paper, we propose an approach for quality inspection of spot weldings using images from laser thermography data.We propose data preparation approaches based on the underlying physics of spot welded joints, heated with pulsed laser thermography by analyzing the intensity over time and derive dedicated data filters to generate training datasets. Subsequently, we utilize convolutional neural networks to classify weld quality and compare the performance of different models against each other. We achieve competitive results in terms of classifying the different welding quality classes compared to traditional approaches, reaching an accuracy of more than 95 percent. Finally, we explore the effect of different augmentation methods., 9 pages,11 figures

Metal additive manufacturing is nowadays a well-established technology for cutting edge applications in the automotive, aerospace, defense and medical sectors. Since additive metal deposition is basically a welding method, which creates parts by successively adding layers of material, there is a chance for defects like pores, cracks, inclusions and lack of fusion to develop. As a matter of fact, interlayer and intralayer defects are often observed in additive manufactured components. However, if one considers the typical end applications along with the high costs involved in metal additive manufactured components, a “zero defect” target is close to mandatory for this technology. Planning an inclusion of the integrity assessment right into the additive manufacturing process would allow for quick corrective actions to be performed before the component is completed. Some effort has been spent in the quest of an efficient in-process flaw inspection, however, no conventional nondestructive testing (NDT) approach has been fully satisfying yet. This work suggests an experimental evaluation of the effectiveness of flying laser scanning thermography, when detecting flaws on an Additively Manufactured acetabular cup prosthesis made in titanium alloy, where some defects have been artificially created. The rough surface scanned is what’s typically left by the additive manufacturing process, and has been left so in order to prove the efficacy of the NDT inspection in real conditions. Potential benefits and limitations of the technique are discussed.

In this work a novel data collection and processing is proposed for the Infrared Non-Destructive Testing (IR-NDT) of interlaminar disbonds on Fibre Metal Laminate (FML) hybrid composites. The adopted active IR-NDT scheme uses a pointwise laser heat source that is moved along a raster scanning trajectory over the object surface. A Focal Plane Array IR camera is employed to acquire the thermal field generated by the moving heat source. Disbonds defect signatures are then searched by analysing the perturbations of the temperature distribution over a reference area following the heat source. The proposed methodology has been implemented on a GLARE sample, since this class of FMLs has gained extensive use in aerospace structures. In particular, a sample of GLARE 1 3/2–0.3 was manufactured in-house, containing triangular shaped artificial disbonds at different interlayers. The novel inspection approach was able to detect the position, size and to some extent the shape of interlaminar defects by recording the changes in standard deviation of the temperature over the monitored area. The sensitivity found in detecting disbonds proposes the presented methodology as a potential alternative to more conventional inspection routes for FMLs.

During manufacturing and operation, different kinds of defects, e.g., delamination or surface cracks, may be generated in the plasma-facing components (PFCs) of a Tokamak device. To ensure the safety of the PFCs, various kinds of nondestructive testing (NDT) techniques are needed for different defect and failure mode. This paper gives a review of the recently developed ultrasonic testing (UT) and laser thermography methods for inspection of the delamination and surface cracks in PFCs. For monoblock W/Cu PFCs of divertor, the bonding quality at both W-Cu and Cu-CuCrZr interfaces was qualified by using UT with a focus probe during manufacturing. A noncontact, coupling-free and flexible ultrasonic scanning testing system with use of an electromagnetic acoustic transducer and a robotic inspection manipulator was introduced then for the in-vessel inspection of delamination defect in first wall (FW). A laser infrared thermography testing method is highlighted for the on-line inspection of delamination defect in FW through the vacuum vessel window of the Tokamak reactor. Finally, a new laser spot thermography method using laser spot array source was described for the online inspection of the surface cracks in FW. Keywords: Plasma-facing components, Ultrasonic testing, Laser thermography, Delamination, Surface crack

The present paper proposes a new procedure to analyze the temperature field distribution during Flying Laser Spot and Laser Line Thermographic scanning (FLST, FLLT) of metallic components, in order to detect vertical surface cracks. The methodology exploits the changes in the temperature field produced by a vertical crack, acting as a barrier towards heat diffusion, when the laser approaches the defect. A number of small regions of interests (ROIs) is placed nearby and around the laser source. The average temperature from each ROI is then monitored during the laser scanning. Vertical cracks can be detected by analyzing and comparing the temperature fluctuations from each ROI when the laser crosses a crack. The paper, in particular, illustrates how the use of multiple ROIs, placed at different locations, may provide additional information that can be used to characterize the defect, and to identify the crack tip location. The approach is validated on plates made of steel and aluminum alloy, where natural cracks have been introduced by fatigue loading, and whose surface has been painted to enhance emissivity. Scratches in the paint have been artificially made in order to analyze their influence on the defect signature. The proposed experimental setup is further simplified by moving the plate samples, mounted on slits, in front of a still laser source and camera head.

Additive manufacturing has been recently employed in industrial sectors with the fundamental requirement for zero defect parts. Technological developments in additive manufacturing notwithstanding, there continues to be a scarcity of non-destructive inspection techniques to be exploited during the manufacturing process itself, thus limiting industrial advancements and extensive applications. Therefore, being able to integrate the defect inspection phase within the additive manufacturing process would open the way to enabling corrective actions on the component in itinere, that is, before reaching the final product. For this reason, new methods of in-process monitoring are gaining more and more attention nowadays. In this work, a remote laser thermographic methodology is employed as a mean to detect micrometric defects in additive manufactured samples. Beforehand, a preliminary Finite Element Analysis was carried out in order to optimize the sensitivity of the technique to the micrometric defects. Our results indicate that the technique is proved to be quite successful in detecting flaws, with the added plus of being suitable for integration in the additive manufacturing equipment, thus allowing a continuous in-line inspection.