As a revolutionary new technique, laser-engineered net shaping (LENS) is a layer additive manufacturing process that enables accurate, rapid and automatic repair of industrial component damage. In the laser repair (LR) process or in service, surface cracks can appear, which have a detrimental effect on the repair quality and the mechanical performance; therefore, the surface crack detection of repaired components has attracted much attention. Laser spot thermography is an important nondestructive testing method with the advantages of non-contact, full-field and high precision, which shows great potential in the crack detection of repaired components. The selection of thermographic process parameters and the optimization of thermal image processing algorithms are key to the success of the nondestructive detection. In this paper, the influence of material properties and thermographic process parameters on the surface temperature gradient is studied based on the simulation of laser spot thermal excitation, and the selection windows of thermographic process parameters for iron-based and nickel-based alloys are obtained, which is applied to the surface crack detection of repaired components. To improve the computational efficiency of thermal images, the Prewitt edge detection algorithm is used in the thermal image processing, which realized fast extraction of cracks with a high signal-to-noise ratio (SNR), and the detection sensitivity of crack width can reach 10 μm. To further study the influence of surface roughness on the thermographic detection, repair layers with and without polishing process are characterized, which show that the Prewitt edge detection algorithm is well applicable to crack detection on surfaces with different roughness level.

The fatigue damage assessment of laser-repaired components is critical to their service safety. However, since laser repairing is an advanced green remanufacturing technology, the current research on its fatigue mechanical behavior and fatigue damage evaluation methods is still immature. In addition, the relevant models used for the fatigue damage evaluation can only indicate the fatigue limit of components, which cannot describe the damage accumulation process of the components during the fatigue testing. Therefore, there is an urgent need to develop a fatigue damage evaluation method that can describe the fatigue damage accumulation and evolution to reveal the damage evolution mechanism during the fatigue test. In this study, based on the 3D-DIC technique, new damage parameters, i.e., strain average value and strain standard deviation, are proposed to quantitatively describe the damage status of the nickel-based components during the stress-based fatigue process. Then, based on the new damage parameters, a strain average value/strain standard deviation damage curve method is proposed to describe the damage status evolution of the components during the fatigue testing and evaluate its fatigue damage. For example, in the tensile fatigue test, the strain average value/strain standard deviation damage curves of the substrate component and the laser-repaired component can be divided into two damage stages. In the first damage stage, the damage increases slowly with the increase in the cycle number, whereas in the second damage stage, the damage increases rapidly with the increase in the cycle number. At this time, there is a demarcation point between the first damage stage and second damage stage in the strain average value damage curve and strain standard deviation damage curve. The cycle number of the demarcation point can be used as a reference value for the fatigue failure of the laser-repaired component. In addition, the electron backscatter diffraction (EBSD) technique was used to verify the validity of the evaluation results from the novel damage parameters.