Three-periodic minimal surface (TPMS) metal porous structure is a new lightweight structure with wide applications in multifunctional structures. In order to study the deformation behavior and energy absorption of different structures, three TPMS samples with Diamond, Gyroid, and Primitive structures were prepared using the selective laser melting technique. Comprehensive analyses showed that different types of TPMS structures have different deformation behaviors and mechanical responses during compression. The results of this article can be used to design impact-resistant parts in vehicles or implants.

The fabrication of aluminum alloy complex components by using laser additive manufacturing process can satisfy the material-structure lightweight and improve the bearing performance. The solidification range of 7075 aluminum alloy is so large that the crack defects are easily caused due to the rapid solidification process of LPBF. And it is seriously limits the application of this alloy. In this paper, the LPBF process was applied to print the 7075 aluminum alloy, and the forming characteristics, solidification and crystallization behaviors, microstructure and properties were analyzed. The influence of melting mode on the microstructure and properties was also studied. In the high scanning speed range (800~2 400 mm/s), there are many cracks and porosity defects existed inside the alloy, and the microstructure is mainly coarse columnar crystals. When the scanning speed is 400 mm/s, the defects are disappeared. With the decrease of scanning speed, the melting mode gradually changed from heat conduction mode to keyhole mode, and the grain size was significantly refined. The mechanical properties of printed parts were greatly improved, and the tensile strength and elongation were 329 MPa and 11.2%, respectively.

Silicon-based materials have been used in electronic microfluidic devices. The heat dissipation effect has become an important index to evaluate their performance, so different process methods have been applied to the patterning processing of silicon-based materials to enhance the heat dissipation performance. The laser etching was used to machine microgrooves on the surface of Si samples in this research. To reduce the thermal influence of laser processing on silicon materials, the ultrashort pulse laser with a pulse width of 12 ps was used to process microgrooves, during which the influence of laser processing parameters such as different laser power and laser scanning times on microgrooves was analyzed. With the help of laser confocal microscopy, the effects of different laser parameters on the depth and roughness of the bottom of the microgroove were studied. The results showed that increasing the laser power and the number of laser scans could effectively increase the depth and roughness of microgroove.

In order to improve the surface hardness and wear resistance of 316L stainless steel, laser melting technology were used to strengthen the surface of 316L steel. The scanning speed of 1 100 mm/min, 1 300 mm/min and 1 500 mm/min were selected to prepare the 316L laser melting layer. The effects of different laser scanning speeds on the microstructure, phase composition, hardness, and wear resistance of the molten layer were studied. The results showed that the 316L laser melting layer was uniform and dense, and the molten layer had no pores, cracks, and other defects. As the scanning speed increased, the grain size of the molten layer gradually decreased. The microhardness of the molten layer prepared at 1 500 mm/min was the highest, about (253±9.8) HV, and the increased in microhardness could be attributed to the synergistic effect of solution strengthening and fine grain strengthening. The laser molten layer prepared at 1 500 mm/min had the best wear resistance, and the friction coefficient and wear rate were the lowest, which were 0.56 and 2.46×106 m3/(N·m), respectively. The wear mechanism was adhesion wear and abrasive wear. Laser melting treatment on the surface of 316L stainless steel can effectively improve its hardness and wear resistance.

WMoTaNb refractory high-entropy alloy coating was prepared on the surface of GH4169 alloy by laser cladding in this paper. The optimal combination of process parameters was determined by regulating two process parameters, namely, laser power and scanning speed. Then SEM, XRD, EDS, microhardness tester and friction and wear tester were used to characterize the microstructure, phase structure, element distribution, hardness and tribological properties of the coating. The results show that the coating is mainly composed of columnar crystals and disordered dendrites, and the main phase structures are BCC phase and Fe-containing phase. There is a mutual dilution and diffusion of elements between the coating and the substrate, forming a relatively good bond. The microhardness of the WMoTaNb coating prepared by laser cladding can reach 1 007.5 HV, and the wear rate at room temperature is only 5.49×10-5 mm3/(N·m), which is far better than the GH4169 alloy matrix. These excellent performances provide more potential possibilities for the performance enhancement and engineering applications of GH4169 alloy.

To address the issue of powder surge in laser cladding carrier gas transportation, a comprehensive simulation analysis was conducted focusing on four key parameters: lifting angle, bending radius, lifting height, and gas flow rate. The study aimed to elucidate the underlying causes of powder surge. The discrete element method (DEM) is used to solve the motion and force of discrete particles, and the computational fluid dynamics (CFD) is used to solve the continuous phase flow field, which is coupled with each other to form a discrete element-computational fluid dynamics (DEM-CFD) model. The simulation results show that the phenomenon of wheezing powder is caused by the position distribution of particles flowing through the elbow. The particles outside the elbow maintain this state until they diffuse in the vertical pipe section, and the particles inside and in the middle of the elbow constantly collide with the wall surface, which leads to different movement time of particles in the elbow section, resulting in a sharp increase in powder amount in a certain period of time. The influencing factors of powder surge are gas flow rate, lifting height, bending radius and lifting angle from large to small. In order to ensure the continuous and stable transportation process, the air flow rate should be greater than 6 L/min, and the transportation should be carried at 45° lifting angle under the condition of meeting the transportation conditions, and the bending radius should be reduced and the lifting height should not be higher than 2.5 m.

To enhance the microhardness and wear resistance of 316L coatings, NbC/316L stainless steel composite coatings were synthesized on 304 stainless steel substrates using laser cladding. The microstructure, phase composition, element distribution, hardness and wear behavior of the composite coatings were studied, respectively. The results showed that the surface of the composite coating had no defects such as cracks and pores, and the structure were uniform and dense. The coating consisted of -Fe and NbC, where NbC were uniformly and diffusely distributed throughout the coating. Combined with the microstructure and element distribution of the coating, NbC played a fine crystal strengthening and second phase strengthening in the coating, and the microhardness of the composite coating were about 354 HV, which was significantly higher than the microhardness of the 316L coating (233 HV). Due to the improvement of microhardness, the friction coefficient and wear rate of the composite coating have been reduced, and the average friction coefficient of the composite coating was about 0.387, and the wear rate was 1.41×10-5 (N·m), which is about 0.5 times that of the 316L coating. The addition of NbC can significantly improve the hardness and wear resistance of the 316L coating.

In order to explore the connection mechanism of 7075 aluminium alloy and CFRTP in the laser welding process, and study the influence of different process parameters on the welding quality, the finite element simulation analysis of temperature field distribution of 7075 aluminium alloy/CFRTP laser high-speed rotary welding was carried out in this paper. The mathematical model and finite element model of aluminium alloy/CFRTP laser high-speed rotary welding were established. The temperature field in the welding process was simulated and analyzed by using finite element software, and the influence of laser power, welding speed, and spot radius on the weld width and penetration was studied. At the same time, an aluminium alloy/CFRTP laser high-speed rotary welding experiment was carried out and compared with the numerical simulation results. The results showed that the finite element model can effectively predict the temperature distribution of the joint during welding. Laser power, welding speed, spot radius, and other process parameters have an important impact on the weld width and penetration. The theoretical simulation results are basically consistent with the experimental results, and the finite element simulation can provide theoretical guidance for achieving high-quality welding between aluminium alloy and CFRTP.

Thermoplastic PMMA has high transparency and chemical stability, and is widely used in automotive doors, windows, lights and other industries. In this paper, carbon black was used as an absorbent to explore the influence of process parameters (carbon black content, line energy density and PMMA thickness) on weld quality (tensile force and weld width) in PMMA laser transmission welding process, and SEM observations were made of weld section morphology with different carbon black content and line energy density. The results indicate that both carbon black content and line energy density initially enhance the welding strength, but excessive levels lead to a decline. In contrast, as PMMA thickness increases, the welding strength also increases, albeit with a gradually diminishing rate of improvement. Notably, all three factors exhibit a positive correlation with weld width. Notably, at an optimal carbon black content of 0.15 wt.% and line energy density of 1.11 J·mm-1, a “ridge-like” cross-sectional morphology is observed, indicating thorough plastic melting and inlaying, thus yielding excellent welding quality.

In this paper, three-dimensional network cellular structure and TPMS structure ceramic skeleton were prepared by light curing 3D printing technology. The metal was filled in the skeleton by no pressure metal fusion method, and the Al2O3/Al composite material of 3D continuous network was successfully prepared. The compression fracture behaviors and main fracture mechanisms of the two structured composites were investigated. The results show that the ultimate compressive strength and energy absorption of the TPMS composite are 260.64 MPa and 791.19 kJ/m3, which are 4.8 times and 15.5 times of that of the honeycomb structure, respectively. Analysis reveals that composite compression failure entails a combination of toughness and brittle fractures. The TPMS structural composite effectively redistributes stress and transfers loads owing to its smooth and regular topology, thus offering enhanced strength and ductility, with promising applications.

Counterfeit and substandard CNC tools pose significant threats to the tool market, prompting interest in traceability and anti-counterfeiting marking technologies. Existing methods, such as pattern engraving, information code labels, and radio frequency tags, suffer from issues of imitation susceptibility, detachment, and high costs, which are problematic for both tool users and manufacturers. To address these issues, we conducted an experiment utilizing laser technology to imprint a 2 mm×2 mm information code on the surface of a cemented carbide tool. The influence of the laser process parameters on the processing quality and reading efficiency of information codes was studied and the optimum process parameters were obtained: the laser power is 9 W, the laser scanning spacing is 30 m, the laser scanning speed is 1 000 mm/s and laser repetition frequency is 980 kHz. In addition, through the readability test of the information code, the influence of the surface damage and error correction, the information code data storage capacity, the distance of the identification device and the identification angle on the identification result was analyzed. In the first and second categories of damage does not affect the reading of the message code, the third and fourth category of damage affects the reading of the message code. Under normal lighting conditions, the message is stored within 6 to 52 characters, the recognition distance is 35 mm to 200 mm and the recognition angle is 90°±25°. The results show that laser marking of small-sized information codes on tool surfaces can satisfy the coding and surface integrity requirements for most precision CNC tools, thereby enabling tool traceability and anti-counterfeiting throughout the manufacturing process.

The distance from power lines to ground is an important indicator for transmission line inspection and power grid risk assessment. However, traditional manual measurement methods are difficult to operate and inefficient due to complex environmental and terrain conditions. Based on UAV LiDAR point cloud data, an efficient intelligent detection technology process is proposed, which includes point cloud classification, bottom-layer transmission line extraction, distance detection to the ground, and risk point identification. The main innovations are: (1) By projecting the three-dimensional point cloud of the transmission line into the two-dimensional residual space, the point cloud segmentation process is transformed into a projection point clustering problem, which dilutes the negative impact of data missing and point cloud noise factors on the fine segmentation of a single transmission line; (2) An identification and extraction strategy for the lowest transmission line is designed based on cluster barycentric analysis; (3) The intelligent detection of transmission line to ground distance is realized based on laser point cloud. The experimental results show that this method can quickly and accurately identify the lowest transmission line from the original point cloud data, and realize the efficient detection of ground distance and accurate identification of risk points. It has the characteristics of simple operation and high automation. This research provides a theoretical and practical reference for safety inspection of airborne LiDAR transmission lines.

This paper addresses the challenges of uneven frame construction, large errors, and poor reconstruction of 3D maps for indoor environments using mobile robots. To address these issues, we introduce Camera Radar Net (CRN), a novel 3D map construction method that integrates LiDAR and RGB-Depth cameras. In CRN, a fusion algorithm of Lidar-Visual Inertial Odometry via Smoothing and Mapping (LVIO-SAM) is proposed, which will optimally estimate the spatial pose of the two-dimensional mobile platform. Then, the spatial pose data and the wheeled odometer are dynamically optimized by the Error State Kalman Filter (ESKF) algorithm to obtain a good mapping effect. Finally, a mobile robot was used for experimental verification. The experimental results show that compared with lidar inertial odometer and visual inertial odometer, the proposed method reduces the size error of 3D map by 22% and improves the odometer accuracy by 0.19% in the construction of indoor environment.

The terahertz frequency band has emerged as a promising candidate for the next generation of satellite communication systems, necessitating thorough investigations into the modeling of space terahertz communication channels. This paper reviews the state-of-the-art in modeling technology for space terahertz communication channels. We commence by outlining the unique propagation characteristics of the terahertz frequency band in space communication systems. Subsequently, we categorize spatial terahertz communication channel models and discuss the crucial factors that must be considered during channel modeling in diverse scenarios. We provide a comprehensive review of the research progress pertaining to each of these factors. Finally, we summarize the current research outcomes and offer insights into potential future research directions, thereby laying the foundation for the integration of terahertz technology into the realm of satellite communications.

To enhance the detection precision of Doppler wind lidar, this study addresses the challenge posed by significant background noise interference in echo signals. A Mahzender frequency detector-based incoherent lidar system is developed, and a comparative analysis is conducted on various denoising methods. The study evaluates the effectiveness of Fourier analysis, FIR filtering, moving average filtering, and wavelet denoising with both soft and hard thresholds. Results indicate that the semi-soft threshold denoising algorithm outperforms other methods, yielding reduced signal noise and smaller root mean square error. Additionally, it effectively integrates time and frequency domains. Thus, employing the wavelet denoising algorithm with semi-soft thresholds is advantageous for lidar applications requiring precise frequency shift measurements for wind speed determination.

In frequency modulated continuous wave (FWCM) measurement system, real-time data processing speed is critical for system responsiveness. At high beat signal frequencies, the vast amount of data acquired significantly increases the time required for fast Fourier transform (FFT) calculations. In this paper, a multi-frequency sampling method based on the Chinese remainder theorem is proposed, which replaces the hardware multi-channel under-sampling by means of software sampling at intervals, realizes the accurate estimation of the frequency of the beat signal, and greatly reduces the calculated data. It has great advantages especially when dealing with high frequency signals. The simulation results prove the feasibility of the method and demonstrate the improvement of the calculation speed of the multi-frequency sampling method.

The primary purpose of an ash silo is to temporarily collect and store fly ash produced by boiler operations, necessitating regular internal environment monitoring. Addressing the challenges of a dusty and visually obscured environment within ash silos, this paper presents a three-dimensional shape reconstruction system utilizing laser scanning technology. The system utilizes a self-developed inverted 3D laser scanning device to capture the original point cloud data of the ash silo. This data is subsequently processed and fed into a 3D reconstruction algorithm to reconstruct the silo′s shape. The system has been tested in a thermal power plant′s ash silo, demonstrating its ability to accurately detect adhesion on the silo′s inner wall and ash deposits at the silo′s bottom.

This paper introduces a point cloud feature point detection method based on a hierarchical clustering algorithm to address the limitations of traditional methods in accurately detecting detailed features and reflecting the true object information. The minimum spanning tree and depth first search algorithm are used to adjust the direction of the normal vector of each triangle formed by each point and its neighborhood points. Non feature points and candidate feature points in the point cloud model are detected by Gaussian mapping of normal vector. For candidate feature points, hierarchical clustering algorithm is used to judge whether they are feature points. Experimental results demonstrate the effectiveness of the proposed algorithm in accurately detecting feature points within scattered point cloud data, including those with unclear details. Specifically, the method detected 810, 933, 2955, and 3941 feature points for the Sheep, Fandisk, Bunny, and Dragon point cloud models, respectively, surpassing the performance of other feature point detection methods.

Shortwave infrared imaging technology is a high-precision, high-resolution imaging technology with broad application prospects in the military field. This article mainly introduces the application progress of shortwave infrared imaging technology in the military, including night vision, reconnaissance and surveillance, remote sensing, remote sensing system, infrared imaging guidance, etc. Through the research and application of shortwave infrared imaging technology, the efficiency and accuracy of military operations can be improved, making important contributions to the security and development of the country and the society.

This paper proposes a method for locating distributed fiber vibration intrusion events using Rayleigh backscattering (RBS) response section boundary combined with air-frequency energy distribution, aiming to address the issue of limited spatial resolution in traditional pipeline leakage monitoring systems due to the width of the detection pulse. The spatial frequency energy distribution is used to display the left boundary of the RBS response section to characterize the exact location of vibration intrusion events. Vibration detection experiments were carried out on the designed phase-sensitive optical time-domain reflectometer (-OTDR) with different width detection pulses, and the characteristics of RBS response section varying with the width of detection pulses were studied. Then, through vibration tests in three different environments, the feasibility and superiority of vibration location by combining air-frequency energy and RBS response section boundary are verified. The experiments show that the location accuracy of the system is 2 m when the sampling rate is 50 MS/s.

Laser imaging entails scanning objects with a laser beam, generating an image based on the reflected beam. However, external noise and redundancy during scanning often distort the laser-reflected image characteristics, impeding recognition accuracy. To address this issue, we propose a laser imaging feature recognition method incorporating visual communication techniques. Specifically, the method first obtains laser imaging characteristics through a vision system calibration process. Subsequently, a convolutional neural network is utilized to denoise the laser imaging features. Finally, a support vector machine determines the classification boundary for the feature samples, and calculates the probability distribution of various samples from this boundary, enabling laser imaging feature recognition. Experimental results demonstrate that the proposed method achieves a recognition time of less than 100 seconds, and maintains a recognition accuracy of over 94% even in noisy conditions. This indicates the effectiveness of the proposed approach in improving the robustness and accuracy of laser imaging feature recognition.

Challenges in point cloud registration arise from noise in captured scene data, often due to environmental lighting and equipment limitations, leading to incomplete scene capture and issues such as low accuracy, slow iteration, and susceptibility to local optima. To address these issues, we propose a point cloud template matching method that leverages an enhanced Fast Point Feature Histogram (FPFH) feature extraction technique. This method uses the characteristics of moving least squares (MLS), which can smooth the fluctuation data and repair the holes in the point cloud, so as to improve the feature weight of the FPFH descriptor and optimize the corresponding relationship between the source point cloud and the target point cloud. Finally, the corresponding relationship is used for the initial registration of sampling consistency (SAC-IA) and the iterative closest point (ICP) registration to obtain the final transformation matrix. This approach demonstrates a 35% reduction in iteration count and an 82% improvement in registration accuracy compared to traditional algorithms when matching the target point cloud within the scene data. The method exhibits high accuracy, robustness, and reliability in point cloud registration tasks.

In order to study the mode characteristics of the external cavity diode laser array spectral-beam-combined system, based on rate equation of the optical feedback diode laser, the coupled cavity oscillating model of the diode laser emitter is established, and the condition of modes that can stably oscillate in the coupled cavity are given, and the oscillation modes that satisfy the phase condition are divided into single mode oscillation (only one mode can stably oscillate in the coupled cavity) and multi-mode oscillation (multiple modes can stably oscillate in the coupled cavity). Combined with the gain curve of the coupled cavity, the mode structures and beam properties of single mode oscillation and multi-mode oscillation are given, and the effects of the structural parameters of the spectral beam combining system on the mode stability are analyzed. The results show that enhancing the reflectivity of the laser′s front surface and reducing the external cavity′s equivalent reflectivity can enhance the spectral combining light source′s modal stability. For arrays with a larger number of diode laser emitters, we reveal from a physical mechanism perspective that utilizing a transform lens with a shorter focal length can stabilize the modes of edge emitters.

Non-line-of-sight (NLOS) imaging technology differs from traditional visual field imaging by enabling the detection of hidden targets beyond the line of sight through advanced optical imaging techniques. This involves capturing information about hidden targets through photon multiple scattering and subsequently reconstructing the target′s image using appropriate algorithms. As such, image reconstruction technology plays a crucial role in evaluating the effectiveness of NLOS imaging systems. In this paper, image reconstruction technologies are analyzed and summarized, and are divided into four categories: classical back projection image reconstruction method, wave field based image reconstruction method, image reconstruction method based on optimization and deep learning reconstruction method, then the characteristics and applicable scenarios are compared and analyzed among the different reconstruction techniques. Finally, the paper discusses the current progress and future prospects of 3D image reconstruction technology in the context of NLOS imaging.

This paper proposes an improved greedy projection triangulation algorithm to address issues such as lengthy processing time, rough surface quality, and hole formation. Firstly, the voxel filter is improved, the optimal voxel grid is calculated with the number of point clouds as the threshold, and the adjacent points of the center of gravity are used instead of voxels to achieve down-sampling. Subsequently, statistical and Gaussian filtering are applied to smooth the simplified point cloud. The octree is adopted to replace the k-d tree for neighborhood point cloud search, and a moving least squares method optimized for octree is utilized for normal estimation, which reduces backtracking time and mitigates normal ambiguity. Finally, based on Delaunay′s spatial region growth algorithm, the plane is used Triangulation, obtaining a triangular mesh surface according to the topological relationship of points in the plane. The experimental results show that, compared with the traditional greedy projection triangulation and Poisson algorithm, the proposed method has better reconstruction surface smoothness and reduces the number of holes while maintaining the algorithm′s speed and local details.