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.

As a promising method for moiré processing, sampling moiré has attracted significant interest for binocular vision-based 3D measurement, which is widely used in many fields of science and engineering. However, one key problem of its 3D shape measurement is that the visual angle difference between the left and right cameras causes inconsistency of the fringe image carrier fields, resulting in the phase mismatch of sampling moiré. In this paper, we developed a phase correction method to solve this problem. After epipolar rectification and carrier phase introduction and correction, the absolute phase of the fringe images was obtained. A more universal 3D sampling moiré measurement can be achieved based on the phase match and binocular vision model. Our numerical simulation and experiment showed the high robustness and anti-noise ability of this new 3D sampling moiré method for high-precision 3D shape measurement. As an application, cantilever beams are fabricated by directed energy deposition (DED) using different process parameters, and their 3D deformation caused by residual stresses is measured, showing great potential for residual stress analyses during additive manufacturing.