As one of the most promising metal additive manufacturing (AM) technologies, the selective laser melting (SLM) process has high expectations ofr its use in aerospace, medical, and other fields. However, various defects such as spatter, crack, and porosity seriously hinder the applications of the SLM process. In situ monitoring is a vital technique to detect the defects in advance, which is expected to reduce the defects. This work proposed a method that combined acoustic signals with a deep learning algorithm to monitor the spatter behaviors. The acoustic signals were recorded by a microphone and the spatter information was collected by a coaxial high-speed camera simultaneously. The signals were divided into two types according to the number and intensity of spatter during the SLM process with different combinations of processing parameters. Deep learning models, one-dimensional Convolutional Neural Network (1D-CNN), two-dimensional Convolutional Neural Network (2D-CNN), Recurrent Neural Network (RNN), Long Short Term Memory (LSTM), and Gated Recurrent Unit (GRU) were trained to establish the relationships between the acoustic signals and characteristics of spatter. After K-fold verification, the highest classification confidence of models is 85.08%. This work demonstrates that it is feasible to use acoustic signals in monitoring the spatter defect during the SLM process. It is possible to use cheap and simple microphones instead of expensive and complicated high-speed cameras for monitoring spatter behaviors.

Laser lap welding of steel and aluminium with different thickness nickel foil was carried out. The effects of nickel interlayer thickness (T_Ni) on penetration depth, phase transition, mechanical properties were investigated. As the T_Ni increased from 0 to 50 µm, the weld penetration depth was first increased and then decreased, reaching a maximum of 382 µm when T_Ni was 20 µm. There was a γ-phase transformed from δ-ferrite in welded nugget and the transformation of high-temperature δ-ferrite into austenite was promoted as the T_Ni increased. The shear resistance of the steel/Al joint reached the maximum value of 103 N mm⁻¹ when T_Ni was 20 µm. Which was almost 92% higher than the strength of the joint without nickel foil added.

Mode instabilities (MI) threshold in the Yb:YAG crystalline fiber amplifier is simulated by a full numerical model. The propagation of signal fields is simulated by the finite-difference beam-propagation method combined with the rate equations, and the time-dependent heat equation is solved by the alternating-direction-implicit method. Considering the strong temperature-dependent laser performance of Yb:YAG, an iterative method is applied to reach the steady state of Yb:YAG, the crystalline fiber amplifier, before the simulation of MI behavior. The simulated MI thresholds in Yb:YAG crystalline fiber amplifiers are found to be at least 28 times of those in Yb-doped silica-glass fiber amplifiers, up to tens of kilowatts. Simulation results show that, in addition to the expected higher thermal conductivity and lower thermo-optic coefficient, strong gain saturation also plays an important role in the high MI threshold of the Yb:YAG crystalline fiber.

An all-in-fiber method of generating orbital angular momentum (OAM) is proposed. A simple device composed with a section of helically symmetric fiber and another section of regular fiber is designed to convert input light to optical vortices. Finite element method calculation of first- and second-order OAM generation based on the coordinates transformation technique is taken to show that the eigenmodes of the helically symmetric fiber structures carry orbital and spin angular momentum. Simulation using the self-developed beam propagation method algorithm is also performed to verify the orbital angular momentum generation and evaluate the performance of the OAM generator.

As the heat load within the central core of Chirally-Coupled-Core (CCC) fibers will change the pre-designed refractive index profile through the thermo-optic effect, its impact on the laser performance of CCC fibers is investigated. Analysis and simulation results on two typical CCC fibers show that the effects of the heat load include the modal loss reduction and the transmission spectrum drift. The former comes from the thermal lensing effect in the central core, and the latter is caused by the change in the refractive index difference between the central core and the side core. Considering the non-uniform axial heat distribution in the actual laser operation, the overall laser performance of CCC fibers with different pump power is simulated. It is found that, because of the high pre-designed high-order mode loss, the single-mode operation of CCC fibers will be maintained but the slope efficiency may reduce dramatically if the fundamental mode loss is strongly dependent on the heat load.