Due to the high precision and high speed of spindles for machining centers, thermal issues cannot be avoided. The temperature rises of the spindle shaft, which is the rotating component, causes issues such as increased thermal displacement in the tool axis direction and an increase in friction torque, leading to limitations on the spindle speed. Heat removal or heat diffusion methods are effective in reducing the temperature of the spindle shaft. The former method of removing heat from the rotating shaft requires complex peripheral devices for cooling. Here, the latter method of diffusing heat is examined. Specifically, a method for reducing the temperature of the high-temperature part and the temperature difference generated in the shaft will be examined.

In order to diffuse the heat of the spindle shaft, it is necessary to increase the thermal conductivity of the shaft. In this study, highly oriented pyrolytic graphite (HOPG), which has recently attracted attention in the semiconductor field, is used for the spindle shaft instead of heat pipes (HP), which are generally used for heat diffusion. The temperatures of the rotor and bearings during rotation of the HOPG spindle shaft and the normal steel spindle shaft were measured. Under the conditions of D_mn value of 1.53×10⁶ mm/min, the hot part of the normal steel spindle shaft is 42°C and the generated temperature difference is 8K. On the other hand, with the HOPG shaft, it was able to reduce to 40°C and the generated temperature difference was reduced to 5K. By using a spindle shaft with high thermal conductivity by HOPG, it was found that the temperature of the high temperature part can be lowered and the temperature difference occurring in the shaft can be reduced.

Aiming at the problem that the basic impedance control has great impact force and is difficult to cope with environmental changes when it contacts with the tooth surface of worm gear, an adaptive impedance control method based on genetic algorithm was proposed. The influence law of spindle speed, feed speed and grinding force on the surface quality of worm gear tooth surface is analyzed. With material removal rate as the optimization objective, an optimization model of grinding process parameters is established based on particle swarm optimization algorithm, and the optimal grinding process parameters for industrial robot grinding worm gear tooth surface knife marks are obtained: Spindle speed (n=3087.82r/min), Feed speed (v_f=0.51mm/s), Normal grinding force (F=19.9N). The experimental results show that the roughness of worm gear tooth surface is increased from 0.941 to 0.719 by using the optimized grinding process parameters. Moreover, this method can effectively suppress the external force influence of industrial robots in the process from free space to constrained space, and the force fluctuation is significantly reduced after contact stabilization, and it has stronger environmental adaptability and force control performance.

In this paper, a Genetic-Artificial Bee Colony Algorithm (G-ABCA) for mechanism optimization synthesis is proposed to improve the accuracy of the dimensional synthesis of the 4-bar mechanism. Firstly, the plane coordinate of the 4-bar mechanism was determined. Then, the relevant design parameters of the link motion were analyzed. The objective function was constructed to minimize the position error between the actual trajectory of the mechanism and the target trajectory, constraints of the 4-bar plane mechanism were added. Then, by means of the improved artificial bee colony algorithm, the length, size and angle variables of the 4-bar mechanism were optimized. The parameters of the classical case were optimized. Finally, the optimization results of the algorithm were simulated for the optimized parameters of the 4-bar mechanism. The results were compared to other optimization algorithms. The results show that the trajectory error obtained by the improved artificial bee colony algorithm is smaller and the optimization effect of the parameters of the 4-bar mechanism is better. The proposed algorithm improves the crossover rate between food sources, extends the population optimization space, improves the local search ability and prevents the premature convergence of the genetic algorithm. The validity and accuracy of the method are proved, which provides a theoretical basis for the in-depth study of the trajectory error of the 4-bar mechanism.

A face gear is typically used in fishing spinning reel mechanism owing to its easy fabrication and good reel handle rotation. As face gears without tooth flank modification are sensitive to assembly errors, the fishing reel sensation becomes unstable in mass production. Previously, tooth flank modification with a transmission error (TE)-controlled curve was used to solve this problem. The TE-controlled curve stabilized the fishing reel sensation for assembling. However, in mass production, the manufacturing error of a pinion and face gear must be considered along with the assembly error. In a previous study, we analyzed all the eight error factors, including the manufacturing error, individually. Thus, we clarified that pressure angle deviation of the pinion and tooth rotational error of the face gear have a significant effect on TE. However, in mass production, these errors are combined in a complicated manner. In this study, an experiment was conducted using the L₁₈ orthogonal array to elucidate the interaction between error factors.

No peaks and troughs were observed in the curve of each factor, thus showing that there is little interaction due to the combination of factors. Although the proposed model was less affected than the conventional model by most errors, the proposed model was affected by the pressure angle deviation of the pinion and the tooth rotational error of the face gear. These results were the same as that of the single-factor experiment in the previous report. By analyzing the path of contact using a three dimensional simulation, we confirmed that uneven TE waveforms were caused by edge contact due to insufficient tooth flank modification. The unevenness in the TE waveform occurred when the factor levels of the assembly and manufacturing errors were large, when these error factors were combined, and when the amount of tooth flank modification of the face gear was small. This phenomenon was regarded as a trochoidal interference, which was caused by the contact of the tooth tip of the pinion, and it was also confirmed using prototype gears. The combination of these errors must be carefully considered in the manufacturing process. Consequently, we have elucidated that avoiding the interference due to combination of errors was significantly important to improve the fishing reel sensation.

In this article, a novel optimal design method for segmented modification of cycloid gear tooth profile was proposed to improve transmission efficiency. Firstly, the cycloid tooth profile under segmented modification was analyzed. Secondly, the mathematical model of the meshing phase angle of the working segment of the cycloid gear with the highest transmission efficiency was established, and such optimization was achieved by the particle swarm algorithm，and the important indexes were calculated and compared with the basic segmented modification method. Finally, the tooth profile of the cycloid gear under the new design method was obtained by numerical solution. To verify the method, the processing technology of cycloid gear is designed, and the comparison of performance testing between the new proposed method and conventional basic segmented modification was conducted and analyzed by the assembled RV reducer prototype in accordingly. The results show the temperature rise of the RV reducer under the optimized method was reduced by 1.2℃ under the rated load, and the torsional stiffness and transmission efficiency were increased by 0.03N·m/" and 1.8%, respectively, compared with the basic segmented modification method, which shows that this method can effectively overcome the disadvantage of low transmission efficiency under the basic segmented modification method.

Aiming at the phenomenon that the glue output of the time-pressure pneumatic dispensing system decreases with the decrease of the glue allowance in the glue storage tube, this paper presents method of a glue allowance prediction for time-pressure dispensing systems. This method takes the gas pressure data sequence and the dispensing pressure value at the outlet of the solenoid valve of the time-pressure dispensing system during dispensing, and uses the deep neural network to predict the glue remaining value in the glue storage tube of the current dispensing system. Moreover, according to the nature of different input data, a network architecture combining Gated Recurrent Unit (GRU) and Fully Connected Neural Network (FCNN) is proposed, and two different neural networks are used to process temporal input data and non-temporal input data. This method solves the problem that the traditional glue dispensing system model and control method cannot obtain the glue residual value in real time. And through the measured data experiments, the algorithm is better than the traditional machine learning model in terms of root mean square error and mean absolute error performance indicators.

Bearing surface quality has significant impact on the working performance and durability of the mechanical transmission equipment. The traditional visual detection methods for bearing surface defects face the problems of weak versatility, low efficiency and poor reliability. In this paper, a deep learning detection method for bearing side face based on data augmentation and convolutional neural network is proposed. Firstly, image expansion based on circle detection and polar coordinate transformation is utilized to facilitate the labeling process and improve the significance of bearing defect area. Secondly, a bearing sample data augmentation method is designed to construct the defect data set. Semi-supervised data enhancement based on local defect features, improved RA strategy, and Mosaic algorithm are used to augment the initial bearing sample data set. Thirdly, an improved Faster R-CNN framework for bearing defect detection is established. The ROI align pooling is used to improve the continuity of output features. The Resnet101 network and Leaky Relu activation function are used to avoid the tiny defect feature loss and function dead zone. Furthermore, the FPN is integrated into Resnet101 to improve the detection precision for multi-scale bearing defects. Experimental results show that the proposed method can effectively achieve accurate and rapid defect detection of bearing surface, with a mAP of 98.18%. The proposed data augmentation strategy and defect detection framework show great application potential in the automatic surface detection of mechanical components.

To effectively reduce the specific fuel consumption of aeroengine and obtain the optimal geometric design parameters of compliant cylindrical intershaft gas film seal(CCIGFS) in the limited design space size, an optimal design method of CCIGFS based on the grasshopper swarm characteristics is established, and the optimal design parameters of CCIGFS for counter-rotating shafts are acquired by this method. In this paper, for the sake of leakage calculation, mechanical characteristics of the seal are analyzed and a fluid-structure coupling model of CCIGFS for counter-rotating shafts is built. This fluid-structure coupling model considers the influences of centrifugal expansion and rotor circular precession. Then, according to this method, the leakage rate with various seal widths and diameters is computed and the function relation of leakage rate with seal width and diameter is obtained by curve fitting method. Furthermore, by changing the design parameters of the seal width and diameter, the functional relation between the mass and the seal width and diameter is obtained by curve fitting method too. Thus, the multi-objective optimization design model about the design variables of the CCIGFS is developed. Finally, the state-of-the-art multi-objective grasshopper optimization algorithm is adopted to obtain the corresponding Pareto frontier, and the geometric structure design parameters of the seal are selected according to the actual situation. This paper provides a complete and systematic method for the engineering design and analysis of CCIGFS in the counter-rotating shafts.

This article aims to reveal the meshing performance on face worm gear drive with the variable worm cone angle and to verify the feasibility of using a cylindrical worm as a replacement for the spiroid worm in face worm gear drive. The meshing functions and tooth surface equations are derived in the given coordinate system, as well as the meshing performance equations of induced normal curvature, lubrication angle, and relative entrainment velocity are presented. The influences of worm cone angle variation on the three metrics are analyzed under the design parameters, and it combined with simulation analysis to verify its correctness. The results of the analysis show that as the decreases of worm cone angle, the meshing characteristic between the tooth profiles on both sides of the transmission has an asymmetric feature. The magnitude of variation of the three metrics that assess the performance of meshing is not obvious, indicating that it is possible to replace the spiroid worm drive with a face worm gear with cylinder worm in some working conditions in the future.

Due to the complexity of body resistance spot welding, there are still problems existing in predicting the quality of resistance spot welding, such as less samples between special welded plates and low welded quality joints point, and the distribution of the dataset changing with the welding conditions. To solve this problem, this paper proposes an algorithm for spot welding quality classification and prediction that distinguishes between multiple types of welded joints. Firstly, dynamic resistance signals of spot welding points with different sheet materials and parameter combinations are collected, and denoising and analysis are conducted. The spot welding feature dataset is obtained from the dynamic resistance signals, and the distribution of feature datasets for different types of welding points and different quality intervals of the same type of welding points is analyzed. Then, principal component analysis (PCA) is applied to reduce the dimensionality of the feature dataset and obtain the principal component dataset. Finally, a backpropagation neural network (BPNN) is used, where the principal component dataset is trained and classified by a Naive Bayesian classifier, with the different quality interval datasets as input and the quality scores as output. Through training and testing of the neural network model, accurate quality prediction is achieved for different types and different quality welding points.

Vertebrates achieve a high degree of flexibility and skillful performance via a musculoskeletal system consisting of multiple joints. These joints are simultaneously driven by some multi-articular muscles, which run over two or more joints and synchronize the musculoskeletal system. However, when multi-articular muscles contract, buckling may occur in the system if each joint is not adequately supported, such as by monoarticular muscles or intervertebral discs, and we previously investigated the stability conditions for avoiding such buckling by calculating the potential energy of the muscle elasticity. Although in our previous work we considered only the muscles themselves, actual animal muscles are surrounded and constrained by fascia, other muscles, and skin, which may also influence the stability of the musculoskeletal system. Based on this characteristic, in this study, we examined the effect of the surrounding elastic elements that constrain the muscle pathway on the stability of the musculoskeletal system. We analyzed the static stability of the system with respect to potential energy using a muscle path restraint model of the serial link mechanism driven by McKibben-type pneumatic artificial muscles. Moreover, we confirmed the analytical result by conducting an experiment using a six-joint serial link robot driven by antagonistically arranged pneumatic artificial muscles. The results revealed that the restraint of the muscle path influences the stability of the system, and that the support of each joint and restraint is critical for the stability of the system.

In a 9-speed transmission, as a key participant of a planetary wheel system, the gear ring will be subjected to elastic deformation as a result of the meshing action, affecting the smoothness of the transmission. Firstly, the time-variant stiffness of helical gears is calculated using the potential energy method, the time-variant characteristics of bending rigidity, shear rigidity and compression rigidity are analyzed; secondly, the time-variant gear ring stiffness is computed using the bending beam theory, in which the change in gear ring rigidity is incorporated into the simplified model of the gear ring, and the circumferential displacement, radial displacement and bending angle of the gear ring is used to calculate the gear ring deformation variables and the time-variant stiffness of the internal gear ring; finally, the time-variant stiffness of planetary helical gear is calculated according to parallel connection theory. Finally, based on parallel theory, the comprehensive time-variant mesh stiffness of planetary helical gears was computed, and the ring stiffness influence on the comprehensive time-variant mesh stiffness of planetary helical gears was analyzed in meshing with single and double teeth. The average difference in the zone is 8.9%. The experiment shows that there are two peak values of tooth ring deformation in a meshing period between tooth ring and gear, and the peak value of tooth ring deformation near the meshing point is larger. At low rotational speed, the predicted strain value of the tooth surface of the gear ring has an average difference of 10.6% and 8.6% from the measured value of strain measuring point No. 1 and No. 2.

Strain wave gear, also known as "harmonic drive" is widely used in the industrial robotics field due to the excellent deceleration performance. The tooth modification of the flexspline faces the requirements of high accuracy and service life. In this paper, a novel spatial tooth profile modification method along the circumferential direction of flexspline for strain wave gear is proposed. The circumferential modification method has a small change of meshing point position and working pressure angle, which is beneficial to maintain the transmission accuracy and improve the service life. In addition, the relation model of spatial motion between hob and flexspline, and the relation between tooth profile and modification quantity are study in the view of engineering application aim to reveal that the principle of circumferential modification is the rotation of the tooth profile along the center of the tooth apex circle. And the feasibility of circumferential modification is verified by a actual machining. Then, two main factors, circumferential modification quantity and radius of flexspline indexing circle are analyzed. Afterward, the novel stepwise modification of the circumferential spatial tooth profile of flexspline is introduced. Finally, a case study of circumferential spatial tooth profile modification of flexspline for strain wave gear is conducted. The case study shows that the maximum distance offset value in circumferential modification is 7.8 μm, which is smaller than the traditional modification value (13.2 μm), and the maximum working pressure angle value is 2.24 °, which is smaller than the minimum value (3.93 °) in traditional modification. And the FEM results and the cross-section tooth pairs comparing with the theoretical model also show the possibility of the proposed modification method.

The high-speed angular contact ball bearing(ACBB) works under the coupling action of temperature field, electromagnetic field and other fields for a long time, so it is easy to produce local faults. In this paper, the quasi-static model of ACBB with local defects is established by considering the influence of thermal effect, high speed effect and elastohydrodynamic lubrication(EHL). Based on the quasi-static model, the friction torque model and friction heat generation model of ACBB with local defects are established, and the influence of multi-factors on the dynamic and friction characteristics of ACBB with local defects is studied. The conclusions are as follows: thermal effect and EHL have a significant influence on the dynamic characteristics of ACBB, and when there are local defects on the bearing surface, it will affect the running performance of the bearing; After considering the influence of many factors, the friction heat generation of the bearing increases, which leads to the increase of the bearing load, and finally leads to the obvious increase of the friction shear stress and friction torque in the non defective area. When the rolling element falls into the defect area, the friction shear stress decreases and is greatly affected by the axial angle of the defect.

With the emerging trend in the production of electric vehicles, many components in the car were also modified. Instead of a large, heavy, and complex internal combustion engine, light, compact, highly efficient electric motors are now being used that are superior in terms of torque to the power plant. The main difference between the body of electric-based and internal combustion engine-based cars is the presence of a battery compartment in the electric car (most often located at the bottom of the car). Moreover, in the transmission of electric vehicles, modern electric vehicles use single-stage gearboxes instead of complex multi-stage gearboxes. In this paper, we attempted to design and test a simple single-stage transmission based on planetary gear (PG) with improved efficiency through gear profile-shift modification. Below is a detailed description of the design method of the planetary gearbox and the development process. The first candidate was the 3K planetary gear without second layer ring gear and the second was the 3K planetary without second layer sun gear. Based on the analytical evaluations, the best sample was designed in SolidWorks, its prototype was manufactured, and bench tests were performed.

In this paper, a novel cutter section is designed, which adds a linear transition section between the fillet and the major cutting edge for the three-faced cutter plate. By deriving the relative motion coupling relationship with the cutter plate, machine and gear blank, the tooth surface point set is solved by using the meshing equation and the mapping relationship with the discretized point set of the blank section. The mathematical model and the meshing model of hypoid gear are established with different cutter parameters. The influences of the multi-segment cutter section on the meshing characteristics of the hypoid gear are researched. The results show that the effect of contact pattern is not obvious of with linear segment. Besides, the peak to peak value of transmission error and meshing stiffness are reduced compared with the traditional cutter section. With the increase of the length of the linear segment, the tooth root bending stress increases and the transmission error and meshing stiffness decrease. The tooth root bending stress decreases and the transmission error and the meshing stiffness are not obvious with the increased of the radius of fillet. Therefore, the proper length of the linear segment and the radius of fillet can reduce the vibration by decreasing the transmission error with guaranteed strength.

The process map area of laser beam powder bed fusion for the nickel-based superalloy Inconel 718 is investigated using high laser power (600-1000 W) and scanning speeds (1500-3500 mm/s). The process map is defined by the surface morphologies (visually inspected) and relative densities of the as-built materials. The effects of the process parameters on the melting and solidification phenomena are observed by high-speed camera imaging, while those on the microstructure of the as-built parts are observed through the scanning electron micrograph (SEM). The process window to build specimens with smooth surfaces and high relative densities was in the laser power range of 700-1000 W and a scanning speed of 1500 mm/s. Notably, the relative density of the specimen built in this process window was slightly lower than that of the specimen built in the current process window of low power (100-400 W) and scanning speed (100-1500 mm/s). High-speed camera observation of the melt pool behavior revealed that the plasma plume was ejected backward in the laser scan direction, and many large spatters were ejected along the plume under the proposed higher power and scan speed conditions. Moreover, the melt pool was unstable, and the laser track displayed an irregular shape. The spatter and unstable melt pool were attributed to the keyhole evolution in the melt pool. The microstructure of the as-built parts presented features similar to those of materials built under the current process window. This research provided process parameters set under high power and scanning speed conditions and enabled the fabrication of dense materials like those produced within the conventional process window. The higher scanning velocity reduces the building time compared to the current process window.

Aiming at the problem of tool wear prediction under small samples, this study proposes a tool condition prediction model based on the Tent-ASO-BP neural network. Firstly, the collected vibration and cutting force signals are denoised, and time-domain, frequency-domain, and time-frequency-domain feature parameters are extracted using techniques like fast Fourier transform and wavelet packet decomposition. Subsequently, based on the principle that tool wear increases with the number of cutting passes, Pearson correlation analysis is applied to select feature parameters with a correlation coefficient of no less than 0.9, indicating a strong correlation with tool wear. Finally, the selected feature parameters are combined into a feature vector, which serves as input for training the Tent-ASO-BP neural network for tool condition prediction. Experimental results demonstrate that the combined approach of Pearson correlation analysis and Tent-ASO-BP neural network exhibits excellent learning capability, enabling effective prediction of tool wear in small sample scenarios. This study contributes to addressing the challenges of tool wear prediction in situations with limited data. By incorporating denoising techniques and extracting relevant feature parameters, the proposed model enhances the accuracy of tool wear prediction. The utilization of Pearson correlation analysis ensures the selection of highly correlated features, further improving the model's performance. The Tent-ASO-BP neural network demonstrates its potential as a reliable tool for predicting tool wear, making it suitable for practical applications. In summary, this study presents a tool condition prediction model based on the Tent-ASO-BP neural network and Pearson correlation analysis, specifically designed for small sample scenarios. The experimental results confirm the model's excellent learning capability and its effectiveness in accurately predicting tool wear under such conditions.

The performance of hourglass worm gear hob is influenced by two features of the rake angle: smaller absolute value and more balanced distribution on the left and right sides of each teeth. To meet the requirements of the rake angle, a method of machining the segmental spiral flute rake faces with a cylindrical milling cutter in different drive ratios is proposed. Firstly, a mathematical model of different drive ratios machining the rake face is established based on the principle of gear meshing. The initial point is determined using the point on the spiral face at the indexing ring position of the cutter tooth machined with a fixed drive ratio. The expression for the drive ratio is then calculated based on the machine movement relationship. Next, the optimum drive ratios were determined by studying the effect of drive ratio on the value of the rake angle and the machining position of the rake face. The design results show a significant improvement compared to the values of the rake angle for the fixed drive ratio. The maximum absolute value drops from 5.3° to 0.57°, and the difference between the rake angles of the two sides on cutter tooth is reduced from 7.47° to 0.15°. This implies that the cutting conditions have been substantially improved. Finally, the machining experiment is conducted. Measurement result shows the minimum difference between the experimental and theoretical values is 0.0167° and the maximum difference is 0.5451°. Verifying the correctness of the theoretical calculation and the feasibility of practical machining.