Preparing a high-quality Co-based alloy cladded layer on the surface of magnesium alloy is challenging and uncommon. In this study, laser cladding technology was employed, and high-throughput experiment methods were utilized. The Co-based alloy cladded layer was successfully formed on the surface of AZ31B magnesium alloy under specific process parameters: P=2 000 W, v=300 mm/min, D=3 mm, S=+10 mm, and Q=20 L/min behind the molten pool. The resulting cladded layer exhibited excellent formability with no cracks, pores, or other defects. The focus of this study was to investigate the surface friction and wear properties of the Co-based alloy laser cladded layer and to understand the mechanisms behind its improvement. The results revealed that the Co-based alloy cladded layer demonstrated a stable running-in state during the friction and wear stage. It exhibited significantly lower maximum friction coefficient (0.571), average friction coefficient (0.268), and wear loss (2.3 mg) compared to the substrate. The strong metallurgical bond between the cladded layer and the substrate prevents large-scale peeling during friction. The cladded layer′s enhanced properties are attributed to the solid solution strengthening effects from the solid solution phase and ordered compounds, as well as the high-hardness carbides that contribute to layer strengthening. Additionally, the varying temperature gradients and solidification rates from the bottom to the top of the cladded layer result in grain refinement, significantly enhancing the microhardness. The average hardness of the cladding layer is approximately 10.8 times that of the magnesium alloy substrate. Overall, these impartments contributed to the remarkable enhancement in the friction and wear properties of Co-based alloy cladded layer.

In order to address the surface failure issue of H13 injection head, and to determine the optimal parameters for preparing iron-based alloy coatings on the surface of H13 steel using laser cladding technology.Taking laser power, scanning speed, and powder feeding rate as the optimization variables, and dilution rate and aspect ratio as the evaluation criteria for the optimal solution. Based on the orthogonal experimental design method, the influence of the three variables mentioned above on the evaluation indicators was studied, and the range analysis method was used to analyze the results of the orthogonal experiment. By using the comprehensive balance method and establishing a linear regression model, the optimal combination of process parameters is determined to be laser power of 1 400 W, scanning speed of 12 mm/s, and powder feeding rate of 1.2 rad/s. The research results show that the iron-based alloy coating generated under the optimal process parameters combination exhibits excellent performance. Through the analysis of the coating microstructure and phase composition, it was discovered that the coating is mainly composed of phases such as -Fe, FeNi3, FeCr, C2Fe5, etc. The hardness of the coating has increased by 34.72% compared to the substrate. It can be indicated that the Fe60 clad powder can produce a high-performance coating on H13 injection heads, meeting their operational requirements.

To repair damaged hydraulic columns and extend their service life, single-layer multi-pass lap cladding of an iron-based alloy was performed on a 27SiMn steel substrate using a semiconductor fiber-coupled laser. The optimal lap rate was determined based on the surface flatness quality index of the cladding layer. Subsequently, the microstructure, hardness distribution, corrosion resistance, and wear resistance of the cladding layer were investigated and analyzed. The results show that under the process parameters of laser power of 2 600 W, powder feeding rate of 15 g/min, scanning speed of 4 mm/s, and overlap rate of 40%, the cladding layer with no crack pore defect, optimal surface flatness and largest cross-sectional area of the cladding layer can be obtained. The microstructure of the cladding layer is cellular crystal, dendrite and equiaxed crystal from bottom to top. The friction coefficient is 18.2% lower than that of the substrate, and the cladding layer is oxidized wear, abrasive wear and adhesive wear. The corrosion resistance grade is 2, which is 2 grades higher than the substrate′s. The corrosion zone is intergranular corrosion, and the corrosion resistance and wear resistance are significantly improved, which provides a scientific experimental basis for laser cladding repair and strengthening hydraulic columns.

M350 martensite aging steel is highly valued for its excellent mechanical properties and processability, making it a promising material for applications in the automotive, metallurgical, and die manufacturing industries. However, traditional manufacturing methods face limitations, necessitating the exploration of advanced fabrication techniques. In this study, M350 martensite aging steel was prepared using laser energy deposition technology, and its microstructure, phase composition, crystallographic properties, and mechanical properties were systematically analyzed. The results show that the microstructure of M350 steel deposited by laser energy is mainly columnar crystals and cell crystals, and the phase composition includes martensite phase dominated by body-centered cubic (BCC) structure and a small amount of residual austenite. KAM analysis showed a high dislocation density (4.61×1016 m-2) within the sample. The mechanical property test results show that the tensile strength of M350 martensite aging steel deposited by laser energy is 1153 MPa±11 MPa, the elongation is 7.56%±0.06%, and the microhardness is 410.3 HV±10.8 HV. Fracture morphology analysis revealed a mixed ductile and brittle fracture feature, including the distribution of tiny dimple and fracture surface. This study provides a new understanding and theoretical basis for the microstructure and mechanical properties of M350 martensite steel deposited by laser energy.

This study investigates the molten pool behavior and mechanical properties of parts produced by selective laser melting (SLM) based on its forming principle. Fluent numerical analysis software was employed to simulate the evolution of the molten pool during the SLM process, predicting the flow state, temperature distribution, and cooling rate. The microstructure, grain morphology, and mechanical anisotropy of the formed parts were analyzed using metallographic microscopy, tensile testing, scanning electron microscopy, and electron backscattering diffraction. The results show that recoil pressure is generated under high input energy density, which causes periodic oscillations in the molten pool, leading to the formation of periodic ripples on the surface of the molten pool. The molding parts of Cobalt-chromium alloy present “fish-scale” shapes in vertical section and feathery shapes in cross section. Based on the high cooling rate process, the crystal grains are refined in both cross and vertical sections, among which the average grain size in the vertical section (2.63 m) is about 1.52 times of that in the cross section. There exists anisotropy in the tensile properties of both cross and vertical section specimens, and the yield strength and tensile strength of the cross-section specimens are 648.84 MPa±16 MPa and 1 134.17 MPa±24 MPa, which are 13.03% and 21.62% higher than those of the vertical section, respectively, but the elongation decreases by 14.96%, presenting the characteristics of high-strength and low-plasticity, and their fracture is quasi-cleavage fracture.

A CoCrFeNiTi high-entropy alloy coating was prepared on the surface of 316L stainless steel using laser cladding technology. The phase composition, microstructure, elemental distribution, nanoindentation characteristics, and wear resistance of the coating were investigated. The addition of Ti resulted in the formation of new body-centered cubic (BCC) phases in the alloy, enhancing the abrasion resistance and hardness of the coatings. The hardness of the CoCrFeNi coating increased significantly from 389 HV to 579 HV with the addition of Ti, corresponding to a 48.84% increase in Vickers hardness. This increase is attributed to the solid solution strengthening effect of Ti and the precipitation strengthening effect of the Laves phase. Wear coefficient curves indicated that the alloys with added Ti exhibited lower wear coefficients and higher wear resistance. The CoCrFeNiTi coating demonstrated reduced wear volume and wear rate compared to the CoCrFeNi coating. The wear mechanism of the CoCrFeNiTi high-entropy alloy coating involves abrasive wear accompanied by adhesive wear.

This study fabricated a single-layer W alloy coating on H13 steel using the pre-placed powder laser cladding method. The optimal process conditions were determined by comparing coating quality under different laser power parameters, and the coating was successfully prepared. The micro-region composition distribution and phase composition of the coating were analyzed by EDS and XRD, and its microstructural evolution was inferred. The wear resistance was evaluated through hardness tests and friction-wear experiments. The results show that the coating prepared at a laser power of 320 W and a scanning speed of 300 mm/min exhibited the best quality, with a small amount of ZrC particles effectively regulating solidification and inhibiting crack formation. Cr and Co were uniformly distributed, while Mo and Ni contents were low. The coating microstructure predominantly consists of irregular white W, gray Laves phase (Fe2W), and black -Fe, with minor amounts of fine Co3Fe7 particles dispersed throughout. The hardness of the coating (1 100-1 300 HV) was significantly higher than that of the substrate (420 HV), and its wear rate was only 50% of the substrate′s. Analysis of the wear tracks revealed that the predominant wear mechanisms of the coating were abrasive wear and adhesive wear, while demonstrating that ZrC particles could effectively enhance the coating′s forming quality, hardness, and tribological performance.

To address issues such as weld crater defects, coating burn-off and rupture, and cracking in tungsten inert gas (TIG) welded galvanized aluminum-magnesium steel plates, as well as to enhance joint strength, galvanometer-scanned laser welding (GSL) was employed for welding zinc-aluminum-magnesium coated steel plates. The GSL joints were comparatively analyzed against TIG joints. The macroscopic morphology, microstructure, and mechanical properties of the welded joints produced by the two different processes were examined using optical microscopy, scanning electron microscopy, and a tensile testing machine. The results indicate that the microstructure of the GSL weld zone consists of acicular and blocky polygonal ferrite along with a small amount of granular bainite. In contrast, the TIG weld zone microstructure comprises irregular blocky ferrite and granular bainite. Furthermore, the higher heat input of TIG welding led to the formation of a Widmansttte structure in the weld metal. Compared to TIG joints, GSL joints exhibit significantly finer grain size and a narrower heat-affected zone, which are beneficial for improving joint performance. The tensile strengths of both GSL and TIG joints are similar to that of the base material. However, the elongation of GSL joints is approximately 6% higher than that of TIG joints, demonstrating superior ductility.

This study proposes a laser quenching bionic texturing process for enhancing the wear resistance of 40Cr steel parts, based on the principles of bionics and laser technology. The physical phase, microstructure, microhardness, and friction properties of the laser quenched bionic units were analyzed, with a focus on the relationship between the spacing of bionic units and their properties. The results show that the microstructure of the bionic unit is martensite and M7C3, and the microhardness is increased by 275%, which has excellent soft and hard bionic structure. The friction coefficient and weight loss of the bionic quenching samples are lower than the substrate. When the spacing is 3 mm, the friction coefficient of the bionic samples is reduced by 11.07% and the weight loss is reduced by 50% with the best wear resistance. The analysis reveals that the wear mechanisms of the soft units are adhesive wear and abrasive wear, while the hard units are abrasive wear. During the friction process, the hard unit resists deformation and changes the motion of the debris; the soft unit cushions the energy and stores the abrasive chips; and it exists a wear equilibrium state. This study provides a practical basis for improving the wear resistance of 40Cr steel parts.

Laser cleaning is a green, safe, and efficient cleaning technology that has been widely applied in various fields, including electronic device cleaning, rust and paint removal, and cultural relics preservation. Although researchers worldwide have extensively explored enhancing laser cleaning efficiency and optimizing the cleaning process, there remains a lack of in-depth systematic studies on the underlying mechanisms of laser cleaning. Understanding these mechanisms is crucial for improving the optimization of laser cleaning process parameters, industrial applications, and the broader promotion of the technology. This paper reviews the interactions between laser and matter and systematically examines the laser cleaning mechanisms for micro-and nanoparticles, rust layers, paint layers, and other substances. These mechanisms include ablation, vibration, thermal stress, phase explosion, and stripping effects. Additionally, potential future research directions in laser cleaning mechanisms are discussed.

Current laser cleaning effect detection technologies are limited by high costs, operational complexity, and insufficient feedback information, restricting their widespread industrial application. To address these challenges, a lightweight semantic segmentation network based on deep learning is proposed for detecting paint removal effects. The model is optimized through techniques like model pruning and cross-platform inference acceleration to reduce parameter count and computational complexity. Finally, a combination of corner detection and edge detection algorithms is used to achieve target localization. A deployment algorithm for the detection system is also designed for experimental verification. Experimental results demonstrate that the proposed segmentation model not only effectively identifies the cleaning status but also provides accurate feedback on the residual paint layer information, facilitating parameter adjustment for continued cleaning, thus meeting the real-time detection requirements in the industrial sector.

To improve the surface anti-reflection performance of titanium alloy, femtosecond laser processing technology was used to process anti-reflection microstructures on the surface of titanium alloy. It was shown that the multiple-scale micro-nanostructures generated on metal surfaces after femtosecond laser ablation, the micrometer-scale light-trapping structures, laser-induced periodic surface structures (LIPSS), and nanoparticles. The micrometer-scale light-trapping structures increase the number of reflections of the incident light waves, LIPSS help to couple the incident electromagnetic light waves, and the nanoparticles significantly absorb the light intensity. The optimal process parameters for femtosecond laser processing of titanium alloy anti-reflective microstructures were investigated.Results indicated that microstructures produced with a laser processing power of 5 W, scanning speed of 1 000 mm/s, and scanning spacing of 30 m exhibited uniform and regular surface morphology. The average groove depth was 47.922 m, and the reflectivity of these microstructures in the mid-infrared band (3 m5 m) was reduced to below 3.5%.

This study analyzes the thermal deformation of high-power laser microchannel water-cooling mirrors by coupling the temperature field, obtained through solving the three-dimensional laminar heat transfer equation using the finite volume method, with ANSYS. The performance of microchannel water-cooling mirrors with plate-fin structures and the effects of plate-fin structure parameters on temperature rise and thermal deformation are investigated.Results indicate that under the specified operational conditions, microchannel water-cooling mirrors with parallel plate-fin structures exhibit larger temperature rise and thermal deformation compared to those with traditional parallel inline structures due to the presence of fluid velocity stagnation zones, which reduce the effective heat transfer area. In contrast, microchannel water-cooling mirrors with fork-row plate-fin structures demonstrate significantly lower temperature rise and thermal deformation than those with traditional parallel inline structures. This improvement is attributed to increased convective heat transfer area and enhanced local convective heat transfer efficiency. Additionally, the heat transfer efficiency of the fork-row plate-fin structure increases with the Reynolds number. This study proposes a new structure for reducing the thermal deformation of high-power laser mirrors.

The structural parameters of urban landscape trees are important information for studying their phenotypes, ecological functions and landscape functions. The measurement cost is high to obtain various structural parameters of a standing tree. By establishing the relationship between tree parameters, it is possible for one parameter to predict another, which can reduce costs. In this study, the portable handheld laser radar scanning system was utilized to obtain high-precision three-dimensional point cloud data of the tree structure in Jinshan Park, Cangshan District, Fuzhou City, with the Ceiba speciosa as the research object.The target object was segmented after the point cloud pre-processing.Then, tree height, diameter at breast height, crown width and height under branches were extracted by human-computer interaction. The Pearson analysis result showed that breast height diameter was significantly correlated with tree height and crown width. Finally, the linear, logarithmic, exponential, power, binomial and trinomial function were used to fit the relationship model between diameter at breast height and tree height, crown width, respectively. According to the sample statistics and consistency test value of the fitting function, the most suitable function model was selected andits generalization ability was evaluated. The results show that the optimum model of tree height-diameter at breast height is H=8.665 36e0.013 13Dand width-diameter at breast height is CW=-38.650 76+4.358 06D-0.127 89D2+0.001 24D3.

Large spatial steel structures have numerous joints, which are susceptible to construction errors and often encounter challenges related to low measurement efficiency during construction. In order to quickly and accurately measure the construction error of structural spherical joints, this paper proposes an intelligent measurement method based on 3D scanning. Firstly, the structural point cloud model is established using 3D scanning technology. Secondly, the study examines the impact of various noise ratios on the accuracy of spherical fitting using the random sampling consistency method. It is found that when the noise ratio for the sphere exceeds 80%, the random sampling consistency method fails to achieve accurate spherical fitting. Based on this, the spherical point cloud is clustered by combining the genetic algorithm. The noise ratio of the clustered point cloud is controlled, and then the clustered point cloud is fitted spherically using the random sampling consistency method. This approach achieves accurate cluster fitting of two spherical nodes in a partitioned point cloud with a noise ratio of more than 95%. Finally, the effectiveness of the proposed method is verified through an engineering example in Haikou.Results show that the method can successfully achieve batch automatic fitting of ball nodes in the overall point cloud model of the structure. It also allows for the acquisition of actual ball node coordinates and assessment of construction errors by comparing them with theoretical values. These findings hold significant implications for improving the efficiency of construction surveys for large-scale spatial steel structure ball joints.

Fringe projection profilometry is widely used in industry and scientific research due to its advantages of non-contact, high precision and easy realization. In order to solve the problem of three-dimensional reconstruction error caused by local overexposure or underexposure of surface fringe images of objects with large reflectivity changes, a three-dimensional topography measurement method based on adaptive multiple exposure is proposed.Firstly, the baseline exposure time is calculated according to the histogram cumulative function, and the fringe pattern sequence is fused into the baseline image. Secondly, the exposure time series is estimated iteratively according to the camera response curve and the number of pixels with high signal-to-noise ratio.Finally, the image sequences with different exposure times are synthesized into new fringe image sequences for three-dimensional reconstruction.The experimental results show that the proposed method can adaptively predict multiple exposure times, overcome the problem of overexposure or underexposure of the fringe pattern of objects, and realize the complete three-dimensional reconstruction of objects with large surface reflectance changes and improve the three-dimensional topography measurement accuracy.

To address issues such as mismatches, low registration accuracy, and low efficiency during the point cloud registration process, this paper presents a point cloud registration algorithm based on local curvature and distance features. The algorithm extracts key points from point cloud data using local curvature information and the weighted distance from center points to their neighbors. Firstly, the K-4PCS algorithm was utilized for point cloud coarse registration, then those key points extracted from a local point cloud using linear least squares algorithm were used to complete precise registration using surface ICP algorithm. The method is tested on multiple sets of point cloud data and the results show that the key point extraction method improves the feature of key points compared to the ISS algorithm and the SIFT algorithm, providing a better basis for subsequent registration operations. In subsequent registration, under the same conditions, the algorithms proposed in this paper has improved efficiency, accuracy, and accuracy by approximately 56% and 57% compared to other algorithms in coarse registration. In precision registration, the efficiency has been improved by about 60%. This method can serve as a reference for point cloud registration scenarios where both efficiency and accuracy are critical.

To address the issues of electromagnetic interference susceptibility and the inability to power conventional electronic angle sensors in high-voltage equipment, a reflective fiber optic angle sensor has been proposed. The sensor operates by rotating a shaft to drive a gear, which in turn actuates a rack mechanism. As the shaft rotates, the reflector on the rack moves horizontally, altering the position of the fiber optic probe. A laser beam is directed towards the reflector, and the intensity of the reflected light, which varies with the rotation angle, is detected through the fiber optic. This intensity is converted into a voltage signal, allowing the determination of the shaft′s rotation angle. The least squares method is used to linearly fit the sensor, establishing a mapping between rotation angle and output voltage. Curve fitting is employed to compensate for nonlinear errors. Experimental results show that after nonlinear compensation, the nonlinear error of the designed angle sensor is reduced from 11.39% to 1.34%, with a measurement error of 0.97.

Sweat latent fingermarks are prevalent trace evidence in forensic investigations, and their age estimation is crucial for case resolution. This study utilizes hyperspectral imaging to capture data from sweat latent fingermarks on common indoor surfaces (glass, plastic, and tile) at varying ages. Three preprocessing techniques (SG, SNV, and SG+SNV) were implemented alongside feature wavelength extraction to develop SVM models for age prediction. The applicability and predictive performance of the models under different conditions were compared. The result demonstrates that the SVM models, combined with appropriate preprocessing and feature extraction of hyperspectral imaging, are applicable for predicting the age of sweat latent fingermarks on indoor common objects. Specifically, the model with SG smoothing combined with SNV preprocessing and SPA feature wavelength extraction showed the best predictive performance on glass and plastic, while the model with SNV preprocessing and SPA feature wavelength extraction performed best on tile. Under optimal conditions, the models achieved RPD values of 1.823, 2.074, and 2.039, RMSEP values of 1.580, 1.491, and 1.417, and R2 values of 0.755, 0.781, and 0.758, respectively, on the three surfaces.

Diode lasers (DLs) serve as adjunctive therapies in periodontitis treatment, leveraging bactericidal, ablative, and biostimulatory effects. Numerous studies support the beneficial clinical effects of DLs in periodontal treatment, but other studies suggest that laser therapy offers no additional advantages over traditional periodontal treatments. This article provides a narrative review of the therapeutic effects and applications of DLs in periodontal disease, systematically introducing the mechanisms of action of lasers and the impact of different parameters on treatment outcomes. Photobiomodulation therapy (PBMT) using DLs has been shown to have short-term clinical benefits for periodontitis. Its mechanisms of action may be related to the antibacterial, anti-inflammatory effects of the laser and the promotion of periodontal tissue regeneration. The effectiveness of using lasers in periodontal treatment remains controversial, possibly due to the lack of standardized laser usage guidelines in each clinical application.