Process parameters in the selective laser melting (SLM) process are crucial for determining the quality and accuracy of as-formed parts, making their optimization a key strategy for enhancing part formation quality and precision. This study designed single-track, single-layer, block build-up, and tensile experiments to improve the forming quality of TC4 alloy parts via SLM by optimizing parameters such as scanning speed, laser power, and scanning space. In the single-track experiment, the effects of scanning speed and laser power on the width of the cladding bead were obtained. Then, five sets of matching parameters of laser power and scanning speed were selected for single-layer experiment by observing the continuity of the cladding bead morphology and measuring the uniformity of the cladding bead width. In the single-layer experiment, the influences of scanning space on surface roughness and surface morphology quality were analyzed. Subsequently, ten sets of process parameters were chosen for block build-up experiment in terms of the surface quality and surface roughness of the cladding layer. In the block build-up experiment, the effects of linear energy density and scanning spacing on the relative density were investigated. In accordance with the relative density of as-formed blocks, three sets of process parameters were selected for tensile experiment. Finally, on the basis of the tensile strength and elongation, the optimal combination of process parameters was selected as follows: laser power 200 W, scanning speed 1.0 m/s, scanning space 80 μm.

Objective The performance of a cladding layer is significantly influenced by its microstructure. This study investigates the microstructure of a hollow ring laser cladding layer by examining the dendrite growth of IN718 alloy through macro-microscopic modeling and simulation, providing insights into the microstructural distribution of laser internal powder cladding layers. Methods Ansys software was used to calculate the temperature field results of the molten pool in the process of hollow ring laser cladding. The temperature field results were transformed by using the dynamic growth condition model of micro-structure, and the transformation results were put into the phase field model of micro-structure evolution modeled by MATLAB. The simulation results of micro-structure evolution in the process of hollow ring laser cladding are obtained and verified by experiments. Results In the process of hollow ring laser cladding IN718 alloy, the solidification process of molten pool is columnar crystal growth. The growth stages are linear growth, interface instability, competitive growth and stable growth. Conclusion With the solidification process, the concentration of the first solidified solid phase region is at the lowest, and the concentration of the later formed solid phase is increasing. When the dendrite growth enters the phase of interfacial instability, a large number of crystal nuclei will be generated at the diffusion interface. At this time, the initial columnar grains spacing is 1.202 μm, The columnar spacing reaches the maximum at the end of solidification is 8.307 μm.

Residual stress in metal Selective Laser Melting (SLM) components, stemming from the inherent repeated thermal cycles, large temperature gradients, and non-uniform microstructures during additive manufacturing, is a critical issue. This study employs a heat transfer model and a crystal plastic finite element model, coupled with temperature and microstructure fields, to investigate the impact of various process parameters on the temperature field and grain size residual stress field of 316L stainless steel SLM components. The results show that in the SLM process, when the laser spot passes through the representative region, the stress concentration area appears near the molten pool and gradually expands to the surrounding area. The average residual stress is mainly tensile stress along the scanning direction and transverse direction, while tensile stress and compressive stress are similar along the construction direction. With the increase of laser power or the decrease of scanning speed, the molten pool volume and the average residual stress increase. Double track intersect scanning compared to double track parallel scanning, the molten pool volume in the second scanning is larger and the average residual stress is smaller.

Laser welding was used to weld 22MnB5 high-strength steel in deep penetration welding and heat conduction welding. Aluminum foil was added on the surface to control the content of Al element in the welds, and the effects of Al content on the microstructure and mechanical properties of 22MnB5 steel welded joints was studied. Results showed that, in both deep penetration and heat conduction welding, an increase in Al content in the weld led to an increase in surface defects such as collapse, undercut, porosity and Al-rich weld slag. The microstructure of the welded joint mainly consisted of lath martensite and α-ferrite, with Al-rich intermetallic compounds (IMCs) disperse near the upper and lower weld toes close to the coating. The Al element homogenization in the weld was better in heat conduction welding compared to deep penetration welding. The microhardness of weld showed higher hardness in weld center and lower hardness at weld edge. With an increase in Al content, the density of α-ferrite increased, then led to a reduction in microhardness. The tensile strength of both deep penetration welded joint were higher than the heat conduction welded joint, especially with Al coating on the upper surface. When the weld Al content is 0.47%, the tensile strength of welded joint is 1 477 MPa.

The ongoing development of modern equipment in China has led to a growing demand for efficient and high-quality welding technologies, particularly for large and complex machinery. Narrow-gap oscillating laser welding technology emerges as a significant future direction in welding, capable of fulfilling these requirements. This paper reviews recent research progress in narrow-gap oscillating laser welding and narrow-gap oscillating laser-arc hybrid welding both domestically and internationally. It also provides perspectives and recommendations for the advancement of narrow-gap oscillating laser welding technology.

Sinusoidal surface texture can effectively improve surface friction performance and coating adhesion performance, to clarify the effects of laser processing parameters on the formability of sinusoidal microtexture, nanosecond lasers were used for texture preparation on 40Cr steel. The structural parameters and forming quality of the sinusoidal texture were characterized using three-dimensional morphometers, SEM, etc. And then, the effects of laser power, scanning speed, pulse frequency, and scanning repetition times on the forming regularity of sinusoidal texture were analyzed. Results show that the structural parameters of the sinusoidal texture increase with higher laser power, pulse frequency, and scanning repetition times, or with lower laser scanning speeds. At the peaks and valleys of the sinusoidal texture, the inner side bulges are larger than those on the outside. To prevent the sinusoidal texture from becoming discrete dimples, the scanning speed should not surpass 1000 mm/s. Maintaining the pulse frequency between 15 kHz and 65 kHz, and adjusting the number of laser scanning repetitions from 3 to 13, can prevent the sinusoidal texture from being blocked by sputtered metal or forming too shallow.

The 532 nm picosecond laser was used to etch the surface of the tantalum-silicon composite dielectric film for precision grooving. The microscopic morphology and elemental composition of the tissue after laser etching were analyzed using optical microscopy, scanning electron microscopy, laser confocal microscopy and energy spectrometry. A three-dimensional ablation model was established to analyze the temperature field of the laser interaction with the tantalum-silicon composite dielectric film. The results show that at a laser energy density of 3.24 J/cm2, the tantalum oxide dielectric film can be effectively removed without causing damage to the silica dielectric film or the substrate, thus achieving controlled-depth laser ablation processing.

This study examines the influence of sandblasting and laser surface texture (LST) treatments on the surface and bonding properties of 7075 aluminum alloy, TC4 titanium alloy, and 05Cr17Ni4Cu4Nb stainless steel. Both sandblasting and two variants of LST treatments were applied to the three substrates. The surface morphology and surface roughness (Sa) were observed and measured through laser confocal microscopy. The surface morphology of treated test pieces were observed by scanning electron microscope and the residual stress of treated and untreated test pieces were measured by residual stress meter. The peel strength of test pieces after pasting the liner were tested by intelligent electronic tension machine. The surface morphology of metal substrates after stripping the liner were observed by visual and stereomicroscope. The results shows that the surface morphology of different substrates after the same sandblasting or LST treatment is obviously different. Sandblasting and LST treatments can introduce residual compressive stress and residual tensile stress on the surface of the three substrates, respectively. And the residual stress changes of 05Cr17Ni4Cu4Nb stainless steel are the most obvious. After two LST treatments, the peel strength between 7075 aluminum alloy and liner reached 0.849 N/mm and 0.78 N/mm, respectively, which increased 333.2% and 298.0% compared with the sandblasted sample, and the peel strength between TC4 titanium alloy and liner reached 0.65 N/mm and 1.3 N/mm, which increased 150.0% and 400.0% compared with the sandblasted sample. In addition to 05Cr17Ni4Cu4Nb stainless steel, LST treatments can increase the peel strength and bond integrity between 7075 aluminum alloy with TC4 titanium alloy with liner.

The nanosecond pulsed fiber laser was used for laser cleaning of contaminants on the surface of copper row chain of tobacco wire cutting machine. The effects of laser energy density, number of scans, spot lap rate and pulse width on the cleaning effect and surface morphology were studied, and the surface roughness, elemental content, Vickers hardness and wettability of the material before and after laser cleaning were measured and analyzed. The experimental results show that laser elastic vibration stripping and thermal expansion effect are the main mechanisms to remove contaminants on the surface of copper chains. The surface contaminants were cleaned under laser parameters with a pulse width of 30 ns, a repetition frequency of 20 kHz, an energy density of 2.66 J/cm2, a lap rate of 65% and a single scan, and the surface roughness of the cleaned material was 2.5 μm, and the surface elemental C and O contents decreased from 46.99% and 31.76% to 14.44% and 4.38%, respectively, while the Cu content increased from 8.41% to 54.37%. By using the above-mentioned laser process parameters, the surface contaminants can be effectively removed without damaging the copper row chain matrix and their resistance to oil adhesion can be improved without reducing the surface hardness.

This paper addresses the issues of low accuracy and environmental susceptibility in existing methods for detecting mixed gas concentrations by proposing a method based on the improved TGWO-ELM (Teaching-Guided Firefly Algorithm optimized Extreme Learning Machine) algorithm, integrated with Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology. The method leverages the extreme learning machine for gas concentration retrieval and employs the TGWO algorithm to mitigate stability issues stemming from the initial weights of the extreme learning machine and the random generation of offsets. The convergence factor′s attenuation formula is also improved to reduce algorithm training time. By simulating a single laser with the central wavelength of 1580nm, the large concentration difference experiment and the experiment of changing temperature condition are carried out for the mixed gas of CO and CO2, and the detection error can be stabilized at about 0.003%. Experiments show that the TGWO-ELM algorithm can effectively improve the detection accuracy, stability and response speed of mixed gas, and has high engineering application value.

Traditional angle measurement methods (laser interferometer angle measurement, autocollimator angle measurement, etc.) cannot measure the dynamic angle of the entire circumference of the measured object in real-time. Therefore, a dynamic angle measurement and compensation method for circular gratings is proposed, which uses a laser gyro goniometer to measure the dynamic angle of the circular grating in real time. Firstly, the turntable is calibrated using a self-calibration algorithm, and then the accuracy of the turntable after calibration is verified to be 7.8 ″ using an autocollimator. Secondly, the laser gyro goniometer and the reading head are synchronously triggered by a synchronous trigger plate, analyze the angular position accuracy of the turntable measured by the laser gyro goniometer at different rotational speeds, find out the rotational speed with the smallest angle error measured by the laser gyro goniometer, and finally use the harmonic analysis method to compensate for the angle error at this rotational speed. The experimental results show that the accuracy of the dynamic angle measurement system of the circular grating angle measurement system is improved from 8 “before compensation to 0.7”.

This study employed differential Raman spectroscopy to analyze 60 drug packaging carton samples, aiming to quantify and qualify the chemical fillers present. A novel method for rapid, non-destructive evaluation of diverse drug packaging materials was developed. The original spectrum is pre-treated by the standard deviation standardization method (Z-Score) and the sample is divided into five categories by the condensed hierarchical clustering algorithm. Classification was performed using a discriminant analysis model, which achieved accuracy rates of 96.7% and 78.3% for different models. Additionally, an artificial neural network model was trained and tested, yielding accuracy rates of 95.35% and 82.35%, respectively. To assess the predictive significance of characteristic wavelengths, a random forest model was also constructed using the same datasets, achieving higher relevance with accuracy rates of 90.8% and 85.0%. The findings demonstrate the non-destructive testing capabilities of differential Raman spectroscopy on various types of drug packaging cartons, as well as the efficiency and speed of the general prediction model, which establishes the groundwork for quick examination and evaluation of drug packaging cartons.

In order to detect the surface crack information of aluminum plate using laser array source, the physical process of the interaction between Rayleigh wave and surface crack of aluminum plate is simulated by finite element method (COMSOL) in this paper when the single-pulse line source and laser array source are acting separately. Based on the thermoelastic mechanism, finite element models are constructed for the excitation of Rayleigh waves on the surface of aluminum plate irradiated by single-pulse line source and laser array source respectively, and the results of both numerical simulation are compared. The physical processes of Rayleigh wave interaction with cracks at different depths on the surface of the aluminum plate are simulated numerically when the laser array source acts, and the signals obtained from laser array sources of each array element are compared; when laser array sources with different line half-widths act, the amplitude and spectra of Rayleigh wave obtained from the excitation of them are compared, and the detection depths of the Rayleigh waves obtained from the excitation of laser array sources with different line half-widths are studied. The findings indicate that the amplitude of the Rayleigh wave changes post-time modulation with an increase in the number of array elements, and the amplitude is proportional to the number of array elements from the laser array source, suggesting a cumulative effect on the Rayleigh wave amplitude. An increase in the half-width of the laser array source line results in an increase in the Rayleigh wave wavelength and an expanded range of crack depth detection.

The oscillating scanning pattern of Livox lidar leads to challenges such as drag deformation and sparse point clouds when scanning and sampling moving objects in real-time. This paper introduces an object detection and classification algorithm designed to mitigate motion distortion and enhance point cloud density. Firstly, the algorithm uses background extraction to separate the background points cloud, and then uses the priori rotation translation matrix to fuse the 5 frames point cloud data. At the same time, it uses the Fast Euclidean Clustering algorithm with dynamic threshold to cluster point clouds. Then the geometry information, intensity, histogram of oriented gradient and other features of the object point clouds are extracted to train the Support Vector Machine classifier to achieve the object classification. Finally, the classification performance of the algorithm is analyzed through evaluation indicators such as the precision and recall. The experimental results show that the algorithm has excellent classification and real-time performance for different objects under the condition that the lidar is deployed in the urban intersection environment.

Optical sensors are extensively utilized in scientific research and various social production and living activities. Traditional optical sensors are limited by their large size and integration challenges, hindering advancements towards miniaturization and portability. Micro/nano optical sensors with small size and easy integration could effectively solve the problems faced by traditional optical sensors, the metasurface optical sensors with the advantages of high design freedom, sensitivity, reliability, and multi-information acquisition will be a feasible path to realize integration and miniaturization optical sensors. Metasurface is a powerful light-field manipulation tool, it’s convenient to achieve the function customization of sensors by directional design of metasurface unit structure. The incorporation of artificial intelligence algorithms and deep learning in the design and optimization of metasurface structures significantly enhances efficiency and accuracy, reducing time costs. Metasurface optical sensors, leveraging their design, functionality, and convenience, hold significant application value and potential in areas such as biological and medical detection, optical switching, and optical computing.

In driverless technology, LiDAR is used to scan and detect the surrounding environment to achieve 3D imaging, target recognition, obstacle avoidance, map construction, and autonomous navigation. Among them, surface feature extraction based on laser scanning point cloud is conducive to the accurate 3D reconstruction of the surface shape of objects, which is a necessary prerequisite and important means for 3D object recognition, obstacle avoidance, and autonomous navigation. Therefore, to effectively extract the surface features of 3D objects from laser point clouds, a combined optimization algorithm for surface feature extraction is proposed in this paper, that is, in the sequence of point cloud processing, a variety of measures are integrated to achieve the optimal processing, to improve the reliability and accuracy of each link processing algorithm. The specific optimization measures are as follows. First, the RANSAC (random sampling consistency) sampling strategy is used to optimize the point neighborhood，Secondly, the Harris-3D algorithm is used to extract key points from point cloud data, and combined with the region growth method based on the angle of the normal vector and Euclidean distance double threshold, the point cloud is segmented by clustering. Finally, feature extraction of the 3D object surface is carried out on the point cloud surface after clustering and segmentation, and feature identification of the 3D object surface form is realized. Through experiments on the extraction and reconstruction of regular surfaces in point clouds, the results show that the proposed integration optimization algorithm can effectively improve the surface accuracy and efficiency of feature extraction of the regular surfaces of the 3D object from point clouds, for the plane, cylinder, cone, the extraction of quadric surface reconstruction error is less than 0.075 mm, and for the spherical surface, the reconstruction error is less than 2 mm. In addition, the experimental verification of the real unmanned laser scanning scene with a large amount of point cloud data is also carried out, which shows that the algorithm also has good surface feature extraction effectiveness, and can effectively realize the recognition and reconstruction of 3D object surface shape.

This paper addresses the challenge of multi-scale mixed noise in track point clouds acquired through 3D laser scanning, which significantly impacts subsequent feature extraction and 3D model reconstruction. An improved bilateral filtering-based denoising algorithm is proposed to mitigate this issue. Firstly, isolated noise is removed by density threshold and connectivity analysis. Then, the track point cloud is divided into feature and non-feature areas using a classification method based on the Euclidean norm of the point cloud normal vectors, and improved bilateral filtering and least squares plane fitting are used to smooth and denoise the point clouds in the respective areas. The experimental results show that for two sets of different track point cloud data, the algorithm achieves better results with P2point values of 1.647 3 mm and 0.953 7 mm, and P2plane values of 1.246 7 mm and 0.903 7 mm, respectively. Furthermore, the algorithm effectively retains track feature information, offering a theoretical foundation for the rapid and precise extraction of track information.

Ambiguity in the calculation of normal vectors during Poisson surface reconstruction of 3D point clouds can lead to errors in the reconstructed surface. This paper introduces a modified Poisson surface reconstruction algorithm designed to address the ambiguity of normal vectors. The algorithm calculates the normal vectors of all input point clouds, selects the point with the smallest curvature as the origin, defines its normal vector as the positive direction, searches for neighboring points using the KD tree, reorients the normal direction of neighboring points, and then regards its neighbor points as the new origin to correct the ambiguity of the normal and complete the overall orientation of the point cloud, and finally the algorithm reconstructs the surface according to the obtained normal vectors. Observations and quantitative analysis show that the algorithm significant reduces the ambiguity of normal vectors and can reconstruct a better surface, reducing the maximum deviation distance errors of three models by 66%, 86%, and 95% respectively.

Metasurface are micro-nano optical devices composed of sub-wavelength unit structures capable of modifying the phase, amplitude, and polarization of light waves through structural design, thereby enabling light field control. Optical sensors detect minute objects by leveraging light-matter interactions based on principles such as absorption, emission, and fluorescence. Metaoptical sensors, which harness the physical and design flexibility of metasurfaces, exhibit superior performance. This paper presents the technical background of metaoptical sensors, elucidates their operating principles, and discusses their diverse application scenarios. It concludes with an outlook on the future development trends of metaoptical sensors.

The phase modulation mode is a critical parameter of the liquid crystal spatial light modulator, with significant influence on the interferometric image quality. In this study, we analyze the impact of mode-mismatch, caused by phase modulation errors in a single modulation cycle, on the interference fringe image quality, based on the modulation accuracy and device structure of the liquid crystal spatial light modulator. Our results demonstrate that improper phase modulation modes, in conjunction with limited modulation accuracy and device structure, can lead to phase shift distribution deviations in the interference fringe image that fail to meet the prescribed accuracy requirements, thus severely compromising image quality.