Micro coaxial unmanned aerial vehicles perform well in various complex environments due to their unique structure and performance advantages, especially in executing tasks with high complexity and confined spaces, such as military reconnaissance, disaster rescue, and other fields. Therefore, the research status and progress of the control mechanism and flight control algorithm of micro high-mobility coaxial UAV are reviewed. In terms of the manipulation mechanism, the attitude adjustment principle and design characteristics of the manipulation mechanism, such as tilt disk, center of gravity offset, lower rudder blade, motor cycle control and electromagnetic coil drive, are introduced, and their size parameters and main characteristics are compared. In terms of flight control algorithms, the principles and applications of traditional control methods and advanced control methods are expounded. Finally, the development characteristics and future trends of micro-UAV are analyzed, and the future trends are prospected, and it is pointed out that the integration and cooperation of multiple manipulation systems will be the future development direction to meet the increasingly diverse and complex task requirements.

The joints of robots often exhibit complex dynamic characteristics such as strong nonlinear stiffness and hysteresis, nonlinear friction, and kinematic transmission errors. These factors significantly impact the positioning accuracy and smoothness of joint movements. Therefore, analyzing joint errors and studying parameter identification methods are crucial. This research uses the PSO-LSSVM algorithm to obtain an accurate Preisach model for robot joints, describing their nonlinear stiffness and hysteresis characteristics. The FFT algorithm is employed to identify the high amplitude components in the kinematic transmission error model. The Levenberg-Marquardt algorithm is used to accurately obtain the Stribeck model, which describes the nonlinear friction characteristics of robot joints. Finally, based on the analysis results of the error models and identification algorithms, experiments were designed to verify the reliability of the models and identification methods. This research can provide references for the subsequent design of high-precision robot joint controllers.

In order to verify the reliability of the loader working device, the static analysis of the new working device was carried out for a new type of working device with eight connecting rods reversed by the loader, and the force of each hinge point in the working device was obtained. The boom, rocker arm, ejector rod and connecting rod of the new working device were flexibly processed by Workbench software, and the rigid-flexible coupling model of the loader working device was established in ADAMS software, and the force at the hinge point of the boom under various working conditions was obtained, and the correctness of the rigid-flexible coupling dynamic simulation of the new loader was verified by comparing it with the static analysis results. The stress-time history of the dangerous nodes of each component in the loader working device is obtained. The stress spectrum of the dangerous nodes of the loader was obtained using the rainflow counting method, and the GoodMan linear equation was used to correct the asymmetric cyclic stress. Finally, the fatigue life is calculated by the modified P-S-N curve. The results show that the new loader working device meets the design requirements and lays a foundation for the lightweight research of the working device.

In order to comprehensively obtain 3T3R parallel mechanisms with weakly-coupled characteristics, a novel synthesis method of weak coupling mergers is proposed. First of all, according to the weak coupled characteristics of the machanism, the structural power matrix, and derive the weak coupled conditions of the spatial freedom driving force on the graphic exercise without work; Secondly, according the relationship between the branches dynamic screw and the driver screw, the relationship between the branches dynamic screw and non-driving screw, the motion composition of each branch chain is obtained, the plane and the space sub -parallel mechanisms are synthesis separately; Further, optimize each branch chain of the synthesis sub-mechanisms, and add motions which does not affect the output movement, that each branch chain can meet the requirements of the final expectations; Finally, the plane mechanism and the space mechanism are combined, and a reasonable branch layout is carried out to complete the combination of six free coupling and coupling combined organization type, obtain several new types of six degrees of freedom (6-DOF) parallel mechanisms. The synthesis method proposed in this paper can be applied to other degrees of freedom for weakly coupled parallel mechanisms type synthesis, and enriches the synthesis theory of parallel mechanisms.

To address the motion instability issues of existing wall-climbing robots in internal/external right-angle transition scenarios, this study proposes a rigid-wheeled magnetic adhesion robot integrated with an auxiliary transition mechanism and investigates its multi-surface motion characteristics and transition mechanisms. First, a static mechanics model is established to derive mechanical equations under right-angle transition conditions, determining the critical adsorption force range for slip-free and anti-tipping failure. Through analysis of the robot’s right-angle transitional states, the influence of discontinuous geometric wall features on adsorption forces during internal/external right-angle transitions is revealed, and the required output torque conditions for the auxiliary mechanism during external transitions are derived. Subsequently, a multi-wheel group coordinated control strategy for internal/external transitions is designed. Furthermore, the functional relationship between air gap spacing and magnetic adhesion force is clarified through magnetic field simulations, and permanent magnet spatial layout parameters are optimized using contact mechanics theory. A prototype is developed and validated through multi-condition experiments, demonstrating that the designed robot exhibits excellent load capacity and wall adaptability. Compared to traditional wheeled structures, its internal/external transition performance is significantly improved, verifying the effectiveness of the structural design, mechanical analysis, and control methodology.

Compared to conventional parallel mechanisms, kinematic redundant parallel mechanisms have more degrees of freedom and rigid body counts, making their dynamic modeling more complex and challenging. Addressing the complexity and computational intensity of the overall dynamic model for the 3-P(RR-RRR)SR kinematic redundant parallel robot, a subsystem dynamic modeling strategy is proposed. Firstly, the branch Jacobian matrix for the driven joint velocity and spherical joint velocity is solved. Then, the velocities of various components within the branch are derived, and a branch subsystem dynamics model is established using Lagrange’s method. Subsequently, the velocities of the moving platform and redundant connecting rod are derived, and the Jacobian matrix between them and the generalized velocities is solved. The virtual work principle is then applied to establish a dynamic model for the moving platform subsystem. After that, a method of mapping virtual forces at the spherical joints to the joint space through the force Jacobian is used to correlate one moving platform subsystem with three branch subsystems, forming an overall dynamic model. The correctness of the model is verified using ADAMS. Finally, based on this subsystem dynamics model, a computed torque controller is designed and applied to the trajectory tracking control of a physical prototype. Compared with PD control, analysis of error data demonstrates that this controller effectively improves the accuracy and response speed of trajectory tracking. The research results provide a reference for in-depth analysis of the dynamic characteristics of the mechanism and the study of control strategies.

In order to meet the development needs of large-scale, lightweight and high storage rate of space optical system sunshield structure, a large-scale special-shaped deployable sunshield structure is proposed. Firstly, according to the shading requirements of the optical system, the overall design scheme of the deployable sunshield structure is studied. Secondly, based on the Accordion origami principle, the folding scheme design of the membrane structure of sunshield is carried out, and a parametric mathematical model of irregular polygonal columnar folding structure is established. Thirdly, the ABAQUS simulation software is used to establish the simulation model of the membrane structure deployable process, and the variation law of the stress during the deployable process is analyzed. Finally, a scale-down prototype is developed, and the deployment function test is carried out. The simulation and experimental results show that the designed sunshield structure can complete the deployment action successfully, the membrane has no interference with the deployable support mechanism, and there is no jam in the deployable process, and the membrane does not tear. The research results can provide certain reference for the structural design and research of other spacecraft sunshield.

Industrial logistics is a significant component of intelligent manufacturing. Forklift mobile robot (FMR) is a typical transporter for intelligent industrial logistics systems and a research focus of mobile robot application in industrial situations. Due to environmental restrictions, operating requirements, and measurement errors of sensors, high-precision positioning is one of the key problems of FMR. Firstly, kinematic model is established under the excitation of the travelling road surface and the positioning error model is established base on the dynamics parameters. Secondly, an update covariance matrix-extended Kalman filter (UCM-EKF) method is proposed to effectively fusion the wheel odometer and LIDAR position information. On this basis, the compensation factor is introduced to the priori covariance matrix to correct the cumulative error and effectively improve the positioning accuracy. Finally, a stacking FMR experiment is conducted to verify the method. The positioning error is reduced from ±33mm to ±13mm. According to experiment results, the positioning error model is accurate and the proposed compensation algorithm is effective. This study will support deep applications in the field of intelligent manufacturing by providing the foundation for FMR's motion control and navigation.

The nose cone configuration of space vehicle plays an important role in the optimal aerodynamic shape of each flight stage. It is found that the structural change of honeybee’s abdomen is consistent with the deformation demand of the variant nose cone of the space vehicle, so the bionic variant nose cone structure can be designed by reference to the deformation of honeybee’s abdomen. By observing and analyzing the deformation motion of honeybee's abdomen, the maximum expansion rate and bending angle of honeybee’s abdomen can be obtained, and a variant nose cone mechanism with better performance than honeybee’s abdomen structure can be designed. Based on the kinematics characteristics of 3-RSR parallel mechanism, 3(3-RSR) series parallel mechanism is designed, and its kinematics theoretical calculation and virtual prototype simulation are carried out. The physical prototype of 3(3-RSR) variant mechanism was manufactured and the shell was designed, and the kinematic experiment was carried out. The experimental results show that the maximum elongation of the mechanism can reach 38.87%, the maximum bending angle can reach 60.172°, the positioning accuracy of the telescopic movement can reach 2.25 mm, and the repeated positioning accuracy can reach ±0.49 mm. The structural expansion rate and maximum bending angle of the prototype are better than that of the honeybee’s abdomen shaped structure, and it has a segmentation structure similar to the honeybee’s abdomen shaped structure, which can meet the optimal aerodynamic shape of the space vehicle at different stages.

Most existing intelligent fault diagnosis studies focus on improving accuracy, implying that decisions are made only by models. From the safety aspect, this over-reliance on models can lead to users having no way of knowing even if the model gives untrustworthy diagnostic results; from the ethical aspect, the current artificial intelligence (AI) technology lacks moral guidance, and the relevant laws are not yet perfect, so it is difficult to pursue responsibility in case of misdiagnosis. A reliable diagnosis model should not only provide as accurate results as possible, but should also point out the possibility of its decision failure to warn the user. Therefore, it is necessary to assess the confidence of the results to mitigate the risk of model failure and to achieve trustworthy fault diagnosis. However, modern deep learning models are often poorly calibrated, i.e., there is a mismatch between the softmax output, which is often considered to characterize the confidence of the result, and the true probability of the result being correct, leading to a significant bias in using it directly as a confidence level. To this end, we propose a calibration technique called adaptive confidence penalty that fine-tunes the strength of the confidence penalty applied to each training sample, which in turn affects the softmax probability of the validation/testing samples inferred by the model. The method compensates for the limitation of the original confidence penalty method that uses a fixed penalty strength without considering the confidence characteristics of each sample, further improving the calibration quality and obtaining well-calibrated diagnosis models. The experimental results illustrate the motivation for designing the proposed method and demonstrate its superiority.

Bolt joints in spacecraft are prone to loosening during vibration tests. If bolt joints loosening are not detected promptly, it may lead to irreparable damage to the spacecraft. Currently, according to industry standards, in engineer, condition monitoring of spacecraft during vibration tests is commonly by observing changes in natural frequencies. However, the linear dynamic characteristics are not sensitive enough to detect early bolt loosening. To enhance the sensitivity of condition monitoring during vibration tests, this study develops a method based on the nonlinear output frequency response function (NOFRF) for detecting bolt joints loosening. This method employs data-driven modeling theory and the generalized associated linear equations (GALE) approach to identify NOFRF, and quantifies the uncertainty caused by noise in the NOFRF identification process by using the Monte Carlo method. Finally, experimental validation demonstrates that this method is more sensitive to early bolt loosening than traditional vibration test condition monitoring methods, thereby enabling more effective early detection of bolt loosening in spacecraft.

With the wide application of pulse width modulation technology and the rapid increase of bus voltage of variable frequency motor, the shaft current damage of high power variable frequency motor has become the dominant factor of bearing failure in wind turbine, rail transit traction motor and other fields. Aiming at the problem of evaluating the micro-damage probability of bearing current in high-power variable frequency motor, considering the influence of micro-roughness of bearing raceway, the calculation method of oil film partial pressure and withstand voltage is proposed, and the EDM breakdown probability model of bearing oil film in variable frequency motor is constructed. The oil film breakdown probability and shaft current density of the non-drive end bearing of 190 kW traction motor are calculated analytically. The modeling results are similar to the shaft current damage in the actual service of the bearing, which verifies the validity and reliability of the model. The results show that the shaft current damage is usually concentrated at the maximum load ball in the Hertz contact area of the inner ring or the outer ring of the bearing, and the possibility of breakdown discharge of the oil film is the highest. The insulating bearing can effectively suppress the breakdown probability of the oil film and the shaft current density by relying on the small capacitance partial pressure and large resistance blocking characteristics of the coating.

Porous media has been proven to be effective in reducing the airfoil noise, but the physical mechanism of the chordwise-varying porous noise reduction and its noise reduction mechanism are not perfect. Nine different types of porous distributions have been designed based on the NACA0012 airfoil, and the scattering characteristics and noise-abatement mechanism of the airfoil under different operating conditions have been investigated and analyzed. The results demonstrate that when the angle of attack and incoming flow velocity are large, the noise reduction effect of the gradient porous trailing edge is better, with a peak noise reduction of 43.68 dB and a maximum total sound pressure level reduction of 19.72 dB. These phenomenon root in the control over the flow characteristics on the upper surface and near the wake. When the pressure difference between the upper and lower surfaces is sufficient to drive the fluid through the porous medium, the fluid will manipulate the flow separation on the upper surface of the airfoil, delay the vortex shedding, reduce the large-scale vortices, control the wake fluctuations, reduce the reverse pressure gradient and reflux zone size, and form a stable shear layer, thus effectively controlling the flow-induced noise sources. Compared to uniformly distributed porous trailing edges, a suitable gradient distributed porous trailing edge can reduce the noise more significantly and can improve the aerodynamic drag and lift.

An engineering issue concerning the substantial performance discrepancy resulting from the linear simulation of the bolted joint interface for cover plate has been addressed. This has been achieved through the integration of finite element modal analysis, experimental modal analysis, and integrated optimization. A novel virtual material layer block modeling and parameter identification technique has been developed, which is tailored to the structural characteristics of cover plate. Additionally, a noise evaluation method has been introduced to facilitate structural design optimization. In response to the non-uniform stiffness distribution of the bolted joint interfaces, an enhanced virtual material layer method has been developed. This method involves the subdivision of the virtual material layer and utilization of surrogate model. The optimization objective is to minimize the average deviation between finite element modal values and experimental modal values, thereby improving the accuracy of the modeling. The optimization focuses on minimizing the maximum equivalent radiated acoustic power within concerned frequency band. This is achieved by ensuring that the multi-order modes in the low-frequency range meet the set value as a constraint. The volume fraction of stiffeners is controlled to preserve a lightweight design. Furthermore, based on manufacturability considerations, topology optimization of cover plate has been conducted. Refining the reinforcement structure based on topology optimization results, a noise reduction has been confirmed through virtual validation and experimental confirmation. The results indicate that the enhanced virtual material layer method has reduced the average deviation of the first six orders of modal frequencies, from 4.29% to 0.12%. Post-optimization, the radiated noise within the frequency band of 1 400-2 200 Hz has been favorably impacted, confirming the efficacy of the developed optimization approach.

As one of the research hotspots in recent years, nanosecond laser welding (NLW) is considered as one of the important processing means of thin foil components, thermal-sensitive components, microelectronic packaging devices and other small-sized high-performance parts because of its high machining accuracy, low heat-affected zone, high peak power, flexible and controllable processing zone, compared with continuous laser. In this review, the research status of paper publication and patent application of nanosecond laser welding is analyzed at first. Secondly, the mechanism, the metal and non-metal material combinations, the influencing factors and the simulation of nanosecond laser welding are mainly described, respectively. Then, the application of nanosecond laser welding is summarized. At last, challenges and research prospective of nanosecond laser welding are discussed.

The peeling force (PF) of the car seat slide rail, an important part of the safety assessment, can comprehensively reflect the safety of the slide rail. The existing PF measuring methods are mainly based on physical tests or numerical simulations, with the problems of high cost, time consumption, incomplete evaluation, and so on. Therefore, we combine numerical simulation and statistical regression to propose a complete PF prediction framework for the automobile seat slide including sensitivity analysis, dataset construction, and force prediction. Firstly, the sensitivity of each geometric variable of the slide rail is obtained by the interpretable linear regression. Secondly, the distance metric is constructed based on the variable sensitivity to evaluate the mutual difference between different working conditions. Thirdly, a reasonable construction scheme of the dataset based on the principle of sparseness is proposed. Finally, iterative local weighted linear regression (ILWLR) is established to achieve an accurate prediction of the slide PF, and the nearest adjacent sample distance is used to quantitatively evaluate the cost of the dataset supplement. Experimental results show that the iterative selection strategy and the weighted distance effectively reduce the model sensitivity to the number of nearest neighbor samples, and the proposed ILWLR method achieves better prediction performance than other local regression methods and statistical learning methods. Besides, considering the cost of data acquisition, an indirect comparison is conducted to verify the superiority of the proposed sparse principle sampling over random sampling in dataset construction. Finally, the mean absolute error (MAE) of the proposed PF prediction framework is 3.3 kN the mean relative error (MRE) is 4.3% in 150 simulated test conditions, and the absolute error is within 2 kN and the relative error is 4% in three physical test conditions, which is excellent for PF prediction task.

The hexapod external fixator is widely used in the treatment of fractures and the correction of skeletal deformities. Synchronized electrical adjustment of its six connecting rods proves advantageous in preventing harmful shear stresses, while measurement of mechanical load-sharing ratios enables monitoring of skeletal growth and healing progress, thereby avoiding bone-end stress shielding to facilitate recovery. An electromechanical hexapod external fixator system is accordingly developed, comprising three primary components: a structural frame, control module, and human-machine interface. An electromechanical structure incorporating built-in motors and pressure sensors is designed to enable automatic rod-length adjustment through control module operation and real-time force monitoring. A mathematical model of the fixator is established, and the fracture reduction algorithm and the calculation method for the axial load-sharing ratio of the fixator are derived, permitting determination of repositioning parameters and load distribution under various installation configurations and deformity conditions. A fixator-fracture simulation model is established to verify the correctness of the fracture reduction algorithm. A femoral fracture reduction experiment is conducted, and the results show that the electric hexapod external fixator system can effectively achieve fracture reduction and monitoring of the fixator’s force.

Equipment maintenance is an important basis to ensure normal production, the existing intelligent maintenance technologies mainly rely on signal analysis, data mining or expert knowledge reuse. However, with the improvement of the automation and integration degree of production equipment, the relationships among the characteristic signals of various operating anomalies, multi-source causes and maintenance schemes present higher fuzziness and complexity, the integration analysis of signals, data and knowledge is the key to improve the accuracy and efficiency of equipment maintenance. Therefore, knowledge graph technology is used to integrate the ternary data of “human”, “cyber” and “physical” to support the abnormal diagnosis and maintenance scheme decision of complex equipment, improve the intelligent degree of equipment maintenance, and avoid the one-sidedness of decision. Firstly, the ternary man-machine object data in the field of equipment maintenance is defined and the ternary ontology design is completed to guide the construction of knowledge graph data layer. Secondly, preprocessing is conducted on the ternary data of human-cyber-physical and a unified joint entity and relation extraction model with mixed attention，MAREL is built to automatically extract knowledge from the ternary data of human-cyber-physical, and to establish associative relationships between them, thereby achieving the fusion of ternary human-cyber-physical data; MAREL dissolves the task into two related decoding modules to solve the entity overlap problem, and the mixed attention mechanism is used to enhance the long text processing capability of the model, the test on the Chinese data set SKE proves that MAREL has excellent performance. Finally, the construction of human-cyber-physical knowledge graph for the maintenance of robot equipment in an automobile production workshop is taken as an example, the effectiveness of the proposed method is verified, results show that the knowledge graph can effectively integrate the ternary data of “human”, “cyber” and “physical”, and provide decision support for intelligent equipment maintenance.

In a compound power-split hybrid powertrain, the performance and fuel efficiency can be further enhanced by engaging and braking the power-split device and power components. To meet the high torque demands of commercial vehicles, traditional wet clutches require an increased number of friction plates and larger size, leading to higher costs and drag losses. In contrast, mechanical clutches are compact and can handle high torque, but they generate friction losses during overrunning, failing to meet the needs of hybrid commercial vehicles for controllable directional locking and bidirectional non-contact freedom. A multi-mode non-contact selectable one-way clutch is designed. This clutch can operate in three modes: forward locking, reverse locking, and bi-directional freewheeling, offering a high torque capacity while avoiding drag and friction losses. The static behavior and mode-switching processes of the multi-mode non-contact selectable one-way clutch are analyzed, and an optimization model was developed with the objectives of increasing the load-bearing torque, reducing transient impacts and achieving a compact and lightweight design, a multi-objective optimization decision-making approach that combines non-dominated sorting genetic algorithm Ⅱ(NSGA2), constrained ordered weighted averaging(COWA) operator, and technique for order preference by similarity to ideal solution (TOPSIS) method is proposed. When compared to initial solution, this optimization method leads to a 23.5% increase in load-bearing torque, a 13.7% reduction in idling angle, and a 0.5% decrease in the volume of key components. A hybrid transmission is mounted on a test bench for mode switching test. The results of the bench test confirm the feasibility of the design method. This study provides valuable insights for the design of high-torque multi-mode non-contact selectable one-way clutch.

Voice coil motors and giant magnetostrictive actuators (GMA) both belong to electromagnetic drive, with good electromagnetic compatibility and complementary advantages. The two structures are nested and integrated to achieve macro and micro integration. How to accurately describe the hysteresis nonlinearity of the giant magnetostrictive material (GMM) in the micro motion system of the macro micro composite actuator, and establish and identify the hysteresis nonlinearity model is the key to improving the positioning accuracy of the actuator. Based on the classic J-A model, this study integrates multiple physical field factors such as magnetic, thermal, and force inside the micro actuator, as well as the influence of the macro magnetic field, and constructs a multi field coupling theoretical model of GMA in the macro micro actuator. Aiming at the parameter identification problem in the hysteresis model, a hybrid algorithm of particle swarm optimization (BAS-PSO) is proposed. This algorithm converts particles in the particle swarm into individuals of the beetle, endowing them with the ability to search. It combines the search speed of BAS and the fine search ability of PSO, and introduces an adaptive algorithm to update the particle swarm weights in the PSO algorithm, improving the global and local optimization abilities. By comparing the simulation results with the measured results, the effectiveness and practicality of the algorithm in the study of magnetic material hysteresis characteristics models have been verified, laying the foundation for achieving high-precision positioning of actuators.

Data-driven models have been widely used to predict the fatigue life of additive manufactured materials because of their powerful capability in high-dimensional nonlinear modeling. However, owing to the high requirement of data support, these models are not economically feasible for many practical cases. To tackle this issue, a transfer learning-based model for fatigue life prediction of additive manufactured materials is proposed, through combining source and target domain data and introducing a clustering-based procedure for hyper parameter optimization. The proposed model can collaboratively model fatigue life using experimental data from different manufacturing conditions, effectively addressing the insufficiency of training data under a single condition and the inconsistency of data distributions under multiple conditions. Experimental results of 316L stainless steel processed by laser powder bed fusion are collected for model verification. The results show that, compared to several degradation models, the proposed model has better prediction performance and lower data requirement, exhibiting promising potential in predicting the fatigue life of additive manufactured materials.

Terahertz metamaterials (THz-MMs) play a crucial role in high-performance terahertz functional devices due to their unique electromagnetic regulatory capabilities. However, the current preparation process for THz-MMs is complex and time-consuming, requiring the combination of various silicon-based micromachining processes and precision equipment, leading to high costs. A femtosecond laser writing method for metal thin films to address these challenges is proposed. By utilizing the minimal thermal diffusion ablation characteristics of femtosecond laser and precise control of pulse energy, the study successfully achieves a single forming process for terahertz flexible metal metamaterials. The effectiveness of the proposed method is demonstrated using a hybrid rectangular aperture flexible metal metamaterial as an example. Experimental results reveal that the femtosecond laser-written metamaterial supports strong coupling between two surface plasma modes and exhibits a high Q value Rabi splitting peak in the transmission spectrum. By adjusting parameter L₂, the frequency of the splitting peak can be tuned from 1.17 THz to 0.97 THz, while the Q value increases from 10.79 to 34.26. These findings suggest that femtosecond laser direct writing technology has the potential to revolutionize the rapid processing of low-cost, high-performance terahertz functional devices.

In our previous studies have found that transverse ultrasonic vibration technology can effectively improve the plasticity of titanium alloy materials. In order to further promote its application in riveting process, Ti-45Nb rivet connection of CFRP laminated as research object are compared and analyzed the connection domain performances by conventional riveting (CR) and transverse ultrasonic vibration-assisted riveting (TUVAR), and the influence mechanism from microscopic characteristics to mechanical properties is revealed. The researched results show that the shear band of the driven head became narrower under the TUVAR process, and the grains deformation is the largest in this region, the grain morphology of the rivet shaft hardly changed. However, the grain boundary angle, grain boundary number and texture orientation of the driven head and rivet shaft had significant changed. The micro-hardness of rivet driven head region 1 increased significantly due to the acoustic residual hardening effect. Comparing with CR’s specimens, the average maximum tensile load of TUVAR’s CFREP titanium riveted specimen is increased by about 4.35%; The relative deformation of the hole after 1×10⁶ fatigue loading of TUVAR specimens are reduced by 28.0% and 23.7% respectively Under cyclic stress levels of 40% F_ult and 50% F_ult, and the residual fatigue strength is increased by 5.3% and 3.2% respectively.

Multicellular structures are a class of cross-scale structures characterized by complex pore features and specific mechanical properties. The intricate topological relationships inherent in the geometrical features of multicellular structures within the design space introduce significant challenges to their formation in the fabrication space. In this paper, in order to break through the self-supporting characteristic design of multi-cellular structures, a multi-cellular structure design method based on the evolution of geometric features is proposed. Starting from the geometric features, the superposition and combination mode of the rod unit is investigated, and the mapping relationship between the spatial position of the rod unit, the single-cell stiffness matrix, and the density of the single cell is analysed, and the two-dimensional and three-dimensional single-cell models driven by the geometric features of the rod unit are established; When employed in conjunction with the topological optimization method, the sensitivity of the multicellular structure is deduced, and the optimization model of the multicellular structure with single-cell matching is constructed. The distribution range of the forming angles of the shared rod units between single cells, as well as the exclusive rod units within a single cell, is analysed in conjunction with the spatial position of the rod units in the cell. The search algorithm for matching the forming angles of the rod units is designed to establish the manufacturing voxel with self-supporting characteristics and realize the self-supporting design of multi-cellular structures. This paper provides a comprehensive illustration of the multi-cellular structure manufacturing voxel construction process through the optimization example of a 2D cantilever beam and a 3D bracket. It also verifies the validity of the proposed method by using the model slicing software of the additive manufacturing equipment. This provides a new theoretical basis and methodological approach for the self-supporting design of multi-cellular structures.

The development trend of high thrust to weight ratio in aviation engines has driven the demand for high-quality machining of turbine blade film cooling holes. On the one hand, ultrafast laser has excellent performance in micro hole machining such as no recast layer and low hole wall roughness due to its approximate “cold machining” properties, and on the other hand, it is widely used in micro and nano machining due to its characteristics of no material selectivity, non-contact, and flexible machining. Therefore, ultrafast laser machining of film cooling holes has become a research hotspot. However, as a typical thin-walled cavity type component, the problem of ablation damage caused by laser penetrating the blade and irradiating the back wall is always difficult to avoid, and the back wall protection technology is also increasingly valued. This article is based on the ultrafast laser processing of film cooling holes. Firstly, it summarizes the ablation mechanism and simulation cases of ultrafast laser micro hole processing, and points out that simulation and experimental comparison constitute the general research route of laser processing; Furthermore, the process routes and specific processing effects of ultrafast laser film cooling hole processing are compared from three aspects: laser parameters, scanning methods, and processing steps; On this basis, the important role of key technologies such as material filling and process control in the processing of high-quality film cooling holes for back wall protection is further summarized. The performance requirements for filling, extraction, and protection of filling materials are clarified, and the feasible ideas and auxiliary positions of process control are determined. Finally, the key goals of ultrafast laser processing research and the systematic and collaborative development trend of back wall protection are pointed out, laying a foundation for the actual processing of film cooling holes.

Aerospace thin-walled parts are prone to machining errors under the action of milling forces due to their complex structures, weak stiffness, and high material removal rates. Machining process optimization and the finite element method provide effective means to solve this problem, but issues such as high economic costs and long computation time still exist. Therefore, an efficient prediction and real-time compensation method for milling force-induced errors in thin-walled parts is proposed. Firstly, to address the large computational load of the finite element method when considering the material removal effect, an efficient prediction method based on stiffness reduction and local update is established. Furthermore, an error compensation value calculation method based on iterative coefficients is proposed to decrease the deviation between the actual and ideal compensation amounts caused by tool-workpiece elastic deformation. Finally, a thin-walled blade milling experiment is carried out. The experiment results revealed that the prediction time for compensation value is decreased by 45.9% compared to finite element methods, and the machining error is reduced by 58.3% after compensation, effectively improving its computation efficiency and machining accuracy.

Fiber reinforced ceramic matrix composites have excellent strength, stiffness, corrosion resistance, high temperature resistance and low density, and can maintain stable performance in a variety of harsh environments. Helical milling process also faces problems such as unclear removal mechanism and poor hole quality. In order to investigate the removal mechanism, damage mechanism and surface quality influence law of 2.5D-C_f/SiC composite during helical hole milling, the removal mechanism of 2.5D-C_f/SiC composite fiber at different angles is analyzed by smooth particle fluid dynamics (SPH) simulation and helical hole milling test. Then the damage mechanism of 2.5D-C_f/SiC composite is revealed through experiments. Finally, the influence of helical milling parameters on the surface quality of hole wall is analyzed by single factor test. The results show that in the helical milling process of 2.5D-C_f/SiC composites, the SIC matrix is mainly brittle and cracked, which is removed by debris. Fiber breakage, fiber wear, fiber pulling damage occurred in fibers at 0° direction, fiber breakage and fiber outcrop occurred in fibers at 45° direction, fiber breakage and fiber pulling out occurred in fibers at 90° direction, fiber pulling out, fiber breakage and fiber outcrop occurred in fibers at 135° direction, and fiber damage at acupuncture direction was similar to fiber damage at 0° direction. The interface phase region produces interface debonding failure. Burr damage and edge collapse damage are the main damage at the entrance and exit of the hole. The surface quality improves with the increase of spindle speed, and deteriorates with the increase of pitch and revolution speed. When the spindle speed is increased from 1 000 r/min to 4 000 r/min, the surface roughness of the hole wall is reduced by 23.76%; when the pitch is increased from 0.1 mm to 0.4 mm, the surface roughness of the hole wall is increased by 38.69%; when the revolution speed is increased from 5 r/min to 20 r/min, the surface roughness of the hole wall increased by 8.1%. This study provides an important reference for helical milling of 2.5D-C_f/SiC composites with high quality hole making.

In order to solve the problem of tooth flank accuracy error that exists when grinding helical gears with worm wheel for topological modification, a topological modification method based on flexible electronic gearbox is proposed. First of all, according to the forming principle of involute tooth flank and topological modification curve, the mathematical models of standard involute tooth flank and double drum modification tooth flank are established. Secondly, the kinematic inverse solution method is applied to derive the additional motions of each axis corresponding to the topological modification tooth flank. Since the multi-axis linkage synchronization control of machine tool in the process of generating gear grinding is realized by the control of electronic gearbox, the additional motion amount is proposed to be added in the control model of electronic gearbox. Finally, numerical simulation of tooth flank modification is carried out to compare the tooth flank deviation obtained by traditional modification method and the tooth flank modification method based on flexible electronic gearbox through two numerical simulation examples. The results show that this method can effectively improve the tooth flank modification accuracy of gear grinding with worm wheel.

The coarse diamond grinding wheel can realize the high-efficiency grinding processing of hard and brittle materials, but its grinding quality is poor, and the truing efficiency is extremely low. The ultrasonic assisted mechanical-chemical truing method is proposed to carry out high efficiency and precision truing for coarse diamond grinding wheel to obtain the truncated protrusive micro grain cutting edges, performing the high efficiency and precision mirror grinding processing of hard and brittle materials of silicon carbide ceramics. Ultrasonic assisted mechanical-chemical truing utilizes the ultrasonic high-frequency friction vibration between diamond and cast iron truing tools and atomic affinity chemical catalytic effect to rapidly remove graphited diamond to realize the efficient precision truing of coarse diamond grinding wheel. Firstly, the influences of ultrasonic truing process parameters including ultrasonic power, truing pressure and truing time on the protrusion homogeneity of #80 coarse diamond grains are investigated; then, the effects of the ultrasonic assisted mechanic-chemical truing parameters and grinding process parameters on the ground surface quality of silicon carbide ceramic are comparatively analyzed. The experimental results show that the ultrasonic assisted mechanic-chemical truing can effectively improve the grain protrusion homogeneity of grinding wheel, and when the ultrasound power, truing pressure, and truing time are 80%, 80 N, and 120 s, respectively, the percentage of the grains with protrusion height ranged from 96～135 μm increases from 69.8% (before truing) to 92.1%. Compared with the traditional mechanical truing, the diamond grinding wheel after ultrasonic assisted truing has better grinding performance and can reduce the surface roughness of silicon carbide by about 84.6%. When the rotational speed N=18 000 r/min, feed speed v_f=10 mm/min, grinding depth a_p=1 μm, the macroscopic ground surface of silicon carbide presents a mirror effect, and its surface roughness R_a can reach 46 nm.

In the process of numerical control programming for complex structural components, the difficulty in reusing machining process knowledge arises due to the heterogeneity of knowledge sources and the complexity of interconnections between knowledge. A knowledge recommendation method for structural parts machining process based on a large language model is proposed. By selecting and fine-tuning the large language model, a vertical domain model of machining process knowledge recommendation for structural parts is established. The evaluation results indicate that the model can recommend corresponding machining processes based on specific part features. To solve the problem of the model not being able to obtain the latest professional knowledge and the low accuracy of machining process recommendations, the LangChain application framework combined with a knowledge base is used to enhance the knowledge retrieval of the domain model and construct a process knowledge question answering system. Through corresponding indicator evaluation, the F1 value of the question answering system improves by 0.026 on the basis of the original domain model, and the accuracy of machining process recommendations is above 90%. In the process decision-making application of CNC programming for aviation structural components, this method recommends corresponding process knowledge based on part features. Compared with the automatic CNC programming system that does not use the method in this article, the efficiency of generating CNC codes for frame type structural components improves to a certain extent, which is of great significance for improving the decision-making efficiency of CNC programmers.