Table of Content

25 December 2025, Volume 36 Issue 12

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Study on Crack Propagation of Freight Train Wheel Treads under Ramp Emergency Braking Conditions

Jie ZHAO, Chun LU, Jiahuan HE, Tinghai MA, Zhang YE

2025, 36(12):  2811-2819.  DOI: 10.3969/j.issn.1004-132X.2025.12.001

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The fatigue crack propagation of freight train wheel treads under ramp emergency braking conditions was studied based on the extended finite element method， taking into account the frictional heat generation， conduction heat dissipation， and the variation of material parameters with temperature. By analyzing the temperature fields and stress fields during the rolling contact processes under ramp emergency braking conditions， the results indicate that the existence of tread cracks affects the wheel-rail contact stress distribution， the high contact stress regions are divided into two sub-regions by the tread cracks， and stress concentration occurs at the crack front， and the tread crack propagation behavior is closely related to the relative positions of cracks and contact regions. During the braking processes， the circumferential compressive stress generated by high temperature will inhibit the tread crack growth， but the residual tensile stress after cooling will promote the tread crack propagation. During the stages of tread temperature rising， the tread crack propagation mode is a mixed Ⅱ-Ⅲ multiaxial propagation mode， dominated by mode Ⅱ propagation. During the stages of cooling， the tread crack propagation mode is mixed Ⅰ-Ⅱ-Ⅲ multiaxial propagation mode， dominated by mode Ⅰ and mode Ⅱ.

Design of Continuum Robots and Compensation Strategies for Losses of Guide Paths

Mingxing YANG, Jiale SHEN, Peng GAO, Xing ZHANG, Junxiang WANG

2025, 36(12):  2820-2828.  DOI: 10.3969/j.issn.1004-132X.2025.12.002

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A novel cable-driven continuum robot and the driving error compensation strategy for guiding paths were proposed to address the problems of low kinematics modeling accuracy and insufficient axial stiffness in current continuum robots. A flexible continuous cutting body with flexible support and a flexible arm structure with enhanced axial stiffness were designed. Subsequently， a kinematics model of the robots was established and the workspace at the end of the flexible arm was obtained. The accuracy of the kinematics modeling was confirmed through bending simulation. Analyzing the causes of bending errors， deriving the transmission losses of the casing and the tension transmission model before and after the rope passes through the disc hole， and then a compensation strategy was proposed for driving loss compensation and kinematics model parameter correction. The bending experiments of continuum robots at different angles show that the maximum bending angle error after compensation is as 4.11°， the maximum position error is as 6.11 mm， and the maximum error reduces 48.0%. The experiments verify the effectiveness of the proposed robots and drive error compensation control strategy.

Conveyor Belt Damages Detection Based on Improved YOLOv8 Algorithm

Yuan YUAN, Yichao BAI, Lidong ZHOU, Wenjun MENG, Miao WANG, Wenbin QU

2025, 36(12):  2829-2836.  DOI: 10.3969/j.issn.1004-132X.2025.12.003

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A conveyor belt damage detection algorithm was proposed based on improved YOLOv8 algorithm. Focal Modulation module was used to replace the original spatial pyramid pooling-fast（SPPF） module. In view of the high similarity between the damage and the background， a DySample dynamic up-sampling module was introduced to make the sampling points concentrate in the target areas and ignore the background parts， so as to achieve effective damage recognition. The efficient multi-scale attention（EMA） module was added to the neck network to obtain more detailed information and further improve the attention of injury targets. The PIoU v2 loss function was introduced to calculate the overlap areas between the real frame and the predicted frame， and the damage location was more accurate. Considering the aspect ratio might better adapt to the damage of different shapes. Experimental results show that the accuracy and mean average accuracy of the improved model for conveyor belt damage detection reach 90.3% and 93.2% respectively， which are 2.3% and 2.5% higher than the baseline model YOLOv8. The improved detection speed of YOLOv8 algorithm may reach 83 frames /s， which may fully meet the needs of real-time detection of conveyor belt damages.

Adaptive Design Method of Efficient Twin Screw Rotors Based on NURBS Mesh Lines

Yuhang GENG, Xueming HE, Zong GAO

2025, 36(12):  2837-2845.  DOI: 10.3969/j.issn.1004-132X.2025.12.004

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To address the issues of cumbersome design processes and challenging performance evaluation in compressor rotor profile design， a reverse design approach for twin-screw compressor rotor profiles was investigated. The rotor meshing line was segmented and fitted using NURBS curves， the control points of each meshing line segment were solved， and an optimization model for the rotor profiles was established. An adaptive optimization design of the rotor profile was achieved by adjusting the coordinates of the meshing line control points using the simplex method. A comparative analysis between the optimized rotor profiles and the original profiles was conducted， along with fluid simulation. The results demonstrate that the comprehensive performance of the optimized rotor profiles is improved by 11.38%. Under three operating conditions， the surface pressure values of the optimized compressor rotors are increased by 5.16%， 5.00%， and 4.93%， respectively， which verify the effectiveness of the adaptive optimization design for twin-screw compressor rotor profiles.

Research on Chemical-assisted Magnetorheological Shear Thickening Polishing of Titanium Alloy Tube Inner Surfaces

Zihao YANG, Zenghua FAN, Xiang ZHANG, Jun GAO

2025, 36(12):  2846-2853.  DOI: 10.3969/j.issn.1004-132X.2025.12.005

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A magnetic shear thickening polishing method was proposed based on chemical assistance， and a novel polishing slurry was designed and prepared. A single-factor experiment was employed to study the impacts of H₂O₂ concentration， pH value， and surfactant concentration on the surface roughness of titanium alloy tube inner surfaces. Under the optimal conditions of 0.1% mass fraction H₂O₂ concentration， pH value of 5， and 0.3% mass fraction surfactant concentration， the value of surface roughness of titanium alloy tube inner surfaces is significantly reduced from 701 nm to 56 nm after 90 min polishing. Scanning electron microscopy and ultra-depth-of-field microscopy reveal that the chemical-assisted magnetorheological shear thickening polishing（CMSTP） may significantly remove the convex peaks and scratches generated during processing， resulting in a defect-free smooth surface.

Multi-objective Optimization of Precision Milling Parameters for Variable Cross-section Scrolls

Xu DANG, Tao LIU, Min YAN, Zhiwei XU

2025, 36(12):  2854-2861.  DOI: 10.3969/j.issn.1004-132X.2025.12.006

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A multi-objective optimization method for precision milling parameters of variable cross-section scrolls was proposed based on the improved NSGA-Ⅱ algorithm. The experiments were designed using the multi-factor orthogonal experimental method to investigate the interaction effects of milling parameters on surface roughness and main milling forces. The regression models of the objective functions were established and validated through goodness-of-fit tests and residual distribution analyses. A multi-objective mathematical optimization model was formulated based on three objectives： minimizing surface roughness， minimizing main milling forces， and maximizing material removal rates. An adaptive crossover and mutation operator was incorporated into the NSGA-Ⅱ algorithm to obtain the pareto-optimal solution set and determine the best combination of milling parameters. Finally， the effectiveness of the algorithm was validated through milling experiments on scrolls. The experimental results indicate that the improved NSGA-Ⅱ algorithm significantly enhances the machining performance. Compared with the non-optimized parameters， the surface roughness of the scroll is reduced by 8.19%， the milling force is reduced by 12.61%， and the material removal rate is increased by 25.81%.

A Key Geometric Error Identification Method for CNC Machine Tools Based on Machining Trajectory Sensitivity Indicators

Xin DAI, Huanlao LIU, Yulin WANG, Xiang LI

2025, 36(12):  2862-2869.  DOI: 10.3969/j.issn.1004-132X.2025.12.007

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A sensitivity analysis method was proposed based on machining trajectories that might identify key geometric errors in CNC machine tool machining processes. Firstly， the spatial error model of the AC dual-turntable five-axis CNC machine tool was completed using multibody system theory and homogeneous coordinate transformation， and the geometric errors were measured using a laser interferometer and ball bar. A spatial error model with the machine tool position as the independent variable was further established， and a new sensitivity index was proposed based on the relationship between the error vector caused by 41 geometric errors in the machining trajectories and the spatial errors. Taking the machining trajectory of the S test piece as an example， 11 key geometric errors were identified. Finally， compensation tests were conducted on the 11 key geometric errors and the remaining 30 geometric errors， respectively. The results show that after compensation for the 11 key geometric errors， the machining errors reduce by 73.63%， while compensation for the remaining 30 geometric errors only reduce the machining errors by 11.28%， proving the correctness and effectiveness of the sensitivity analysis method.

Application Research of High-precision Sensing Mechanisms Based on Pressure Amplification

Lejun HE, Yi XI, Wen LIU, Xiang YAN, Mingjie XIN, Chaoyang WANG

2025, 36(12):  2870-2874.  DOI: 10.3969/j.issn.1004-132X.2025.12.008

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Aiming at the problems of delayed shut-off response in existing gas self-closing valves under leakage conditions， based on pressure amplification a high-precision sensing mechanism was integrated into the valve body as a pilot control mechanism， utilizing the pressure amplification effects to achieve high-precision sensing and actuation.Through FLUENT flow field simulation， the dynamic mechanism of the pressure amplification unit's effect on the pressure sensing region was revealed， clarifying the overcurrent shut-off mechanism whereby minute flow changes trigger an exponential pressure drop surge. A gas leakage experimental system was constructed for validation. The results indicate that the gas self-closing valve equipped with the mechanisms may accurately shut off at a flow rate of 1.211 m³/h， with a deviation of only 0.0107 m³/h from the theoretical set value. The pressure drop mathematical model predicts accurately， showing a mean absolute percentage error（MAPE） of 4.19% between theoretical and experimental values， demonstrates the effectiveness of the pressure amplification unit applied in gas self-closing valves.

Geometric Parameter Optimization Method of Honing Wheels for Lower-noise Texture

Xu ZHANG, Congbo LI, You ZHANG, Chenghui ZHANG, Feng ZHOU

2025, 36(12):  2875-2884.  DOI: 10.3969/j.issn.1004-132X.2025.12.009

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To address the noise issues caused by the near-coincidence of partial tooth surface textures with transmission contact lines during the honed gear transmission， the optimization method of honing wheel geometric parameters for lower-noise textures was conducted. Firstly， the influencing factors of honed tooth surface texture distribution were analyzed， and the model of texture distribution on the honed gear transmission contact line was established. Secondly， based on the finite element method， the influences of the position relationship between the tooth surface texture and the transmission contact line on the noise were analyzed. Then， a lower-noise honed tooth surface texture distribution strategy was proposed， and a honing wheel geometric parameter optimization model for lower-noise texture distribution was established. The case study shows that the gear processed by the optimized honing wheel exhibits decreased energy density in the vibration Campbell diagram compared to the original， and the noise level decreases significantly with increasing rotational speed. These results verify the effectiveness of the method.

Design and Kinematics Modeling of Extensible Snake-like Manipulators

Xuhao WANG, Wolong SHENG, Mengli WU, Yilong XU, Xiaowei ZHAO, Yiran CAO

2025, 36(12):  2885-2893.  DOI: 10.3969/j.issn.1004-132X.2025.12.010

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A novel snake-like manipulator was proposed， the modular joints of the manipulator were designed with an active extensible degree of freedom， which increased the overall motion flexibility and adaptability in complex spaces. Kinematics modeling of the snake-like manipulators was carried out. The mappings among actuator space， joint space and end task space were analyzed. Considering the characteristics of the extensible joints， two novel joint-end inverse kinematics algorithms were proposed， i.e. the integrated method by combing the conventional FABRIK algorithm with Jacobian-based iterative algorithm， and the modified FABRIK algorithm with iteratively updated link lengths. Numerical simulations were conducted to verify computational accuracy and efficiency. The results show that both methods have better accuracy， while the modified FABRIK algorithm has higher computational efficiency. Finally， a prototype was constructed， and experiments were carried out to validate motion capabilities of the proposed snake-like manipulators.

Numerical Simulation and Experimental Analysis of Propeller Flow Fields and Motor Temperature Fields in High-altitude Environments for UAVs

Boyu FU, Zehua XU, Kangshuai LI, Haoyu WANG, Jiaqi HE, Qiang HE

2025, 36(12):  2894-2902.  DOI: 10.3969/j.issn.1004-132X.2025.12.011

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Based on an X2212-type air-cooled permanent magnet synchronous motor for UAVs， a combined approach of numerical simulation and experimental validation was employed to systematically analyze the influence of propeller-induced airflows on the motor temperature fields under three altitudes （510， 2560， 4280 m） and three rotational speeds （4000， 6000， 8000 r/min）. A motor temperature testing platform was constructed to measure the motor temperature rise distribution under different operating conditions. These measurements were compared and analyzed with the simulation results to validate the model's accuracy. The paper finds that as the altitude increases， the maximum motor temperature exhibits a decreasing trend under all three rotational speeds. However， the motor's relative temperature rise increases with increasing altitude. The results indicate that the combined effects of reduced air density， decreased atmospheric pressure， and changes in ambient temperature due to altitude variation synergistically affect the motor's temperature changes. With increasing altitude， the decrease in ambient temperature causes an overall downward trend in motor temperature. Nevertheless， the thinning air weakens the cooling capacity of the propeller-induced airflows， resulting in a decline in the motor's cooling efficiency and an increase in the relative temperature rise.

A Design Method of Wide Blade Ultrasonic Sonotrodes for Both of End and Side Faces Working by Cooperating Frequency Offset Compensation with Stepwise Hierarchical Optimization

Yuqin GUO, Hang YIN, Dongjie YANG, Chenxi LIU, Fuzhu LI

2025, 36(12):  2903-2910.  DOI: 10.3969/j.issn.1004-132X.2025.12.012

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In order to meet the functional requirements of the ultrasonic vibration assist integrated heating/molding processes（UVAIMPs） of thermoplastic FMLs for a variable-dimensional ultrasonic machining system， a novel design method by cooperating the frequency offset compensation with stepwise hierarchical optimization was put forward. After the stepped wide blade ultrasonic sonotrode designed by using the above method was assembled with the specified ultrasonic generator and transducer， the corresponding vibration characteristics were measured with a laser vibrometer. The results show that the above sonotrode may operate stably at a resonance frequency of 20 101 Hz. Under the 50% output power of ultrasonic generator， the maximum vibration displacement reaches 16 μm on end faces and 12.7 μm on lateral faces under the condition that the amplitude uniformity is larger than 90%， and the corresponding effective working regions are 110 mm×30 mm and 110 mm×16 mm. Thus， the sonotrodes with both of end and side working faces are realized to satisfy the demands of the variable-dimensional ultrasonic machining system for UVAIMPs of thermoplastic FMLs. The present work verifies the feasibility and effectiveness of the proposed design method.

Dynamics Modeling and Base Dynamics Parameter Determination of 6-UPRU Parallel Manipulators

Tao NI, Yahui ZHAO, Zeren ZHAO, Kaiqiang YANG

2025, 36(12):  2911-2919.  DOI: 10.3969/j.issn.1004-132X.2025.12.013

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To address the challenges in applying the dynamics model of parallel manipulators， the 6-UPRU parallel manipulators were focused on to investigate the precise dynamics modeling and base dynamics parameter determination. Firstly， a detailed kinematics analysis of the manipulator's moving components was conducted. Subsequently， the precise dynamics model was derived using the Newton-Euler method， and through the proposed model linearization rules， which was transformed into a linear form with respect to the dynamics parameters. Then， a fifth-order Fourier series-based exciting trajectory satisfying physical constraints was designed， with the goal of minimizing the condition number of the observation matrix. Furthermore， by performing QR decomposition on the observation matrix， the base dynamics parameters were successfully extracted， reducing the number of dynamics parameters from 29 to 17， effectively addressing the issue of parameter redundancy. Finally， the correctness of the theoretical model was validated through force-fitting experiments conducted on the SimMechanics and ADAMS simulation platforms and the prototype's base dynamics parameter identification experiments.

Design of Adaptive Self-balancing Control Algorithm for Variable Height Dual-wheel-legged Platforms

Lei ZHANG, Congnan YANG, Weiyi LI, Yijie ZHAO, Xiaocong WANG

2025, 36(12):  2920-2926.  DOI: 10.3969/j.issn.1004-132X.2025.12.014

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A two wheel platform was equipped with drive wheels at the end of the leg structure， which had both high passability on paved roads and high maneuverability on off-road roads. In order to enhance the adaptive ability of the platform， the dynamics model of the platform was established， and linearized at the equilibrium point， according to the characteristics of the linearized equation of state， the state variables were expanded based on the principle of integral control， and the expanded state space model was established. The LQR （linear quadratic regulator）method was used to obtain the feedback control law， the simulation model was built， the physical prototype was trial-produced， and the simulation and experimental research were carried out. The results show that the proposed feedback control rate may well realize the self-balancing of the platform， and the expanded state variable may also well balance the change of the center of gravity position， and realize the adaptive equilibrium control of the platform variable heights.

Investigation of Factors Influencing Expandable Tubes Milling Based on SPH-FEM Coupling Algorithms

Min LUO, Congjian HUANG, Qiaozheng LI, Tingting XU, Yanbo FU

2025, 36(12):  2927-2935.  DOI: 10.3969/j.issn.1004-132X.2025.12.015

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Under formation pressure， expandable tubes deform， restricting the wellbore diameter and causing stuck drilling， which affected production. Milling was required to remove these deformed tubes， but the milling results were influenced by multiple factors. The mill， expandable tube， casing， and cement sheath were taken as research objects. Considering the geometric nonlinearity of expandable tube milling and the contact nonlinearity between the expandable tubes and abrasive particles， a nonlinear dynamics model and numerical calculation method for expandable tube milling were established using the SPH-FEM coupling algorithms. Comparison with literature data verified the model， showing an average grinding force error of 8.84%. The effects of milling dimensions， abrasive particle shape， and surfacing material on the milling performance were examined. Results show that the milling depth should not exceed 0.6 mm； the milling thickness should not exceed 0.8 mm； dodecagonal prism particles provide the best performance； and YG8 alloy is the most suitable surfacing material.

Tool Wear Monitoring Based on IWOA-IECA-BiLSTM Model

Zhenke BAO, Huajun CAO, Fengze QIN, Zhixiang CHEN, Guibao TAO

2025, 36(12):  2936-2943.  DOI: 10.3969/j.issn.1004-132X.2025.12.016

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To improve the monitoring accuracy of tool wear during machining， a BiLSTM model based on IWOA and IECA mechanism was proposed. Tool wear data segments from the PHM2010 dataset were intercepted， and multi-domain features were extracted. Tool wear strongly correlated features were then obtained by screening with the Pearson correlation coefficient. The input features were used to train the model. The BiLSTM module in the model effectively captured temporal features within the data. The IECA attention mechanism module enhances the feature representational capability. The IWOA module optimized the model's hyperparameters， further improving the model accuracy. The model performance was finally tested based on three-fold cross-validation and compared with several other models. The results demonstrate that the IWOA-IECA-BiLSTM tool wear monitoring model achieves the best performance on most test sets. On test sets C₁，C₄ and C₆， the root mean square error （RMSE） values are as low as 6.5， 12.46， and 9.28， respectively.

Multi-step Ahead Real-time Prediction of Tool Wear Based on YOLOv11-Seg and Transformer Model

Yufeng XIAO, Chaoyong ZHANG, Saixiyalatu, Yifan MENG, Chuanjun ZHU

2025, 36(12):  2944-2951.  DOI: 10.3969/j.issn.1004-132X.2025.12.017

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To address the problems of low prediction accuracy， poor generalization capability， and difficulty in achieving real-time prediction of tool wear states in traditional methods， a multi-step forward real-time prediction method for tool wear was proposed by integrating the YOLOv11-Seg model with a Transformer model. An on-machine monitoring experimental platform for tool wear of CNC machines was constructed， and PMC programming was employed to realize automatic cutting of tools and automatic photographing of wear regions. An improved YOLOv11-Seg model was adopted for tool wear measurement， where the CoordAtt coordinate attention mechanism and the Shape-IoU loss function were introduced to improve the accuracy of wear region segmentation. Based on tool wear time-series data and real-time wear measurement data， an improved Transformer multi-step forward real-time prediction model was established under the MFTWP mode， where the residual error correction mechanism was introduced to enhance the accuracy and stability of MFTWP mode prediction. The proposed model was tested on both of public datasets and experimental datasets， and was compared with traditional prediction models. The results show that the proposed multi-step forward real-time prediction model exhibits high accuracy and good generalization capability.

Fault Diagnosis Method of Rolling Bearings Based on Improved Refined Composite Multiscale Sample Entropy and Bayesian Network

Zhaojing TONG, Pengchao WANG, Yongkui FAN, Guangyang HAN, Ziqi WANG

2025, 36(12):  2952-2959.  DOI: 10.3969/j.issn.1004-132X.2025.12.018

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To address the issues of traditional MSE， such as the loss of feature information during the coarse-graining processes and the difficulty in extracting feature information from fault signals at large scale factors， a method for rolling bearing fault diagnosis was proposed based on improved refined composite multiscale sample entropy（IRCMSE） combined with an AOA optimized Bayesian network. The traditional coarse-graining processes， which involved averaging， were replaced with a cross-sampling method to obtain time series at each scale， and the method of calculating entropy values at different scales was changed to extract feature information from the time series. IRCMSE was used to extract the fault feature information of rolling bearings， forming fault feature samples. These fault feature samples were then input into the Bayesian network model optimized by AOA for fault recognition. The improved method is experimentally compared with fault diagnosis methods based on MSE， multiscale dispersion entropy， and refined composite multiscale sample entropy （RCMSE）， verifying the feasibility of the proposed method and demonstrating a higher fault recognition rate.

High-precision Computation of Inverse Kinematics for Redundant Robots Based on Flow Model

Feng YIN, Xin HUANG, Jiayi ZHOU

2025, 36(12):  2960-2967.  DOI: 10.3969/j.issn.1004-132X.2025.12.019

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To improve the accuracy of deep neural networks in solving inverse kinematics for redundant robots and reduce the probability of self-collision solutions， a solution method was proposed based on the conditional normalizing flows model. An improved L-M algorithm was employed to perform secondary optimization on the initial solutions generated by the conditional normalizing flows model to enhance computational accuracy. Furthermore， by training a multi-layer perceptron with extracted self-collision prior knowledge， a self-collision solution detector was constructed to filter out self-collision solutions. The results demonstrate that the calculated positional and angular errors remain below 0.01 mm and 0.1° respectively， the self-collision rate is maintained under 0.1%， and the single computation time is consistently within 10 ms. This method enables efficient and stable solutions for inverse kinematics problems in redundant robots.

A Small-sample Defect Detection Method for Screen-printed Characters with Adaptive Target Region Extraction

Xinyu HU, Junwei ZHANG, Jia AI, Yunling LI, Shuang YAN

2025, 36(12):  2968-2977.  DOI: 10.3969/j.issn.1004-132X.2025.12.020

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The defect detection of screen-printed characters on electronic devices faced problems such as poor segmentation accuracy caused by reflective materials， difficulty in adaptively locating and extracting target regions due to uncertain image poses， and low recognition accuracy caused by small defect detection targets and insufficient samples， an adaptive target region extraction method for few-shot screen-printed character defect detection was proposed. Based on OTSU method an adaptive dual-threshold segmentation algorithm was designed to reduce information loss in bright target regions on reflective material surfaces， achieving accurate segmentation of images with uneven illumination. An adaptive target region localization， extraction， and angle correction algorithm was proposed to solve the problems of precisely locating and extracting adaptive target regions despite variations in character sizes and poses. A method involving preliminary defect target recognition and secondary fine recognition for low-confidence small target characters was studied， achieving accurate recognition for small-target， few-sample defect detection targets. Experimental results demonstrate that： the dual-threshold segmentation algorithm achieves accurate segmentation of character images under uneven illumination； the accuracy of adaptive target region localization and angle correction reaches 99.5%； the character classification recognition rate of the lightweight deep learning model reaches 99.1%； the character defect detection accuracy reaches 98.6%； and the detection speed is as 0.083 seconds per image. These results meet the requirements for both of precision and speed in industrial online detections.

A Multi-fault Diagnosis Method for Rolling Bearings Integrating Two-dimensional Convolutional and GRU

Xiong ZHANG, Lecong DONG, Wenqiang WANG, Weiying QU, Shuting WAN

2025, 36(12):  2978-2985.  DOI: 10.3969/j.issn.1004-132X.2025.12.021

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Aiming at the problems of difficulty in diagnosing and classifying single or compound faults of rolling bearings under complex working conditions，a bearing fault diagnosis method was proposed by fusing two-dimensional convolutional neural network（2D-CNN）and GRU.Firstly，the 2D-CNN layer and GRU layer were used to extract the spatial and temporal features，and the batch normalization（BN） layer was introduced to prevent overfitting.Secondly，the spatial and temporal information features extracted by weight fusion were synthesized，and then the global average pooling layer was used instead of the flatten layer.Finally，the covariance matrix and t-SNE algorithm were used to visualize and analyze the model training processes and output the results by activation function Softmax classification.The model was verified by prognostics and health management（PHM） dataset and XJTU-SY dataset，and compared with other models，the good accuracy and generalization of the model were shown.

A Six-axis Robotic Arm Path Planning Based on Improved SAC Algorithm

Jiying TUO, Xiaonan XU, Jun LI, Yuchen ZHANG, An HUANG, Du HU, Zilin LIU

2025, 36(12):  2986-2992.  DOI: 10.3969/j.issn.1004-132X.2025.12.022

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To improve the convergence speed and training stability of the SAC（soft actor-critic） algorithm， an improved SAC algorithm was proposed， incorporating the concepts of advantage functions and reward centering. To validate the performance of the improved SAC algorithm， simulation analyses were conducted in a six-axis robotic arm path planning scenario， comparing with DDPG（deep deterministic policy gradient）， TD3（twin delayed deep deterministic policy gradient）， and the original SAC algorithm. The results show that the improved SAC outperforms DDPG， TD3， and SAC in both of the convergence speed and stability. After 1500 training episodes， the path planning success rate increases by 4.8% compared to the SAC algorithm. Further experiments confirm the feasibility and effectiveness of the improved SAC algorithm's planning results in real-world environments.

A Full-position Welding Pool Identification and Deviation Measurement Method Based on DeepLab-EMCAD

Yecheng XIONG, Haisheng LIU, Zhongren WANG, Tielin SHI, Hai XIA, Hongbo YANG

2025, 36(12):  2993-3001.  DOI: 10.3969/j.issn.1004-132X.2025.12.023

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A method for full-position welding pool identification and deviation measurement was proposed based on DeepLab-EMCAD. A lightweight MobileNetV3 network was adopted as the backbone of the model encoder， and the atrous spatial pyramid pooling（ASPP） module was optimized to reduce the model parameters and improve the segmentation efficiency. The EMCAD multi-attention mechanism was integrated into the decoder to enhance the segmentation accuracy of the welding pools. A deviation calculation method was proposed to quantitatively describe the deviation based on the segmentation results of the welding pools. Experimental results show that compared with the baseline model， the proposed model improves the average intersection over union and average pixel accuracy in welding pool segmentations by 5.72% and 5.5% respectively， and the inference time is reduced by 29.69 ms， with the number of parameters decreasing by 4.854×10⁷. Compared with classic segmentation networks， the proposed model has the best performance in handling the edges of the welding pools. The deviation detection errors are controlled within 0.1 mm.

NURBS Curve Interpolation Methods for Laser High-speed and High-precision Machining

Yuxin FENG, Jian LIU, Honggui DENG, Qiang YU, Zhan WANG, Haoquan YE

2025, 36(12):  3002-3009.  DOI: 10.3969/j.issn.1004-132X.2025.12.024

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To address the challenges of dynamic computation of NURBS curves in real-time systems， a real-time NURBS curve interpolation method was proposed based on acceleration-continuous ramp-up and ramp-down planning. The curves were interrupted at the curvature extrema， and reasonable connection speeds were assigned through preprocessing. S-curve velocity planning was employed throughout to ensure continuity of speed and acceleration， with controllable acceleration peaks. Experimental results demonstrate that the proposed methods achieve single-axis acceleration continuity. During the processing with NURBS curves， the losses of smoothness in single-axis speed caused by frequent curvature changes were effectively handled， and continuous variations in single-axis acceleration were maintained throughout the machining processes， significantly reducing peak values of single-axis acceleration. Under the same laser machining equipment， the proposed interpolation planning method exhibits higher efficiency and accuracy than that of traditional methods， resulting in improved workpiece quality.

Strength-ductility Synergy Control of Key Overflow Components of Hydro- turbines by Follow-up Hot-hammering-assisted Wire Arc Additive Remanufacturing

Xiaochen XIONG, Yan ZHOU, Xiangman ZHOU, Haihua WU, Lin HUA, Zeqi HU, Xunpeng QIN, Shaohua DENG

2025, 36(12):  3010-3016.  DOI: 10.3969/j.issn.1004-132X.2025.12.025

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The wire arc additive remanufacturing of key over-flow components of hydroturbines was prone to the formation of coarse grains and high residual stress， severely compromising the mechanical properties of the repaire layers. The introduction of the follow-up hot-hammering-assisted（FH） processes in the preparation of thin repair layers might significantly enhance strength but tended to reduce ductility. To address the problems， a strategy of FH-assisted single-pass multi-layer additive manufacturing was proposed to achieve the synergy control of strength and ductility in additive layers. Based on the optimal FH processing parameters， the single-pass multi-layer additive layers were prepared， followed by opticl microscope， X-ray diffraction and mechanical property testing. The effects of the FH processes on microstructure and mechanical properties of the additive layers were studied， and the underlying mechanism was revealed. The results indicate that under the FH processes during single-pass multi-layer additive manufacturing， the additive layers achieve simultaneous improvements in strength and ductility. In the rolling direction， the yield strength and tensile strength increase by approximately 18.7% and 13.5% respectively， while the elongation is basically the same compared with the as-deposited group. In the normal direction， the yield strength and tensile strength increase by approximately 15.2% and 9.1% respectively， with the elongation being improved by 14.9%. The mechanism of synergy control of strength and ductility in additive layers is as follows： the grain refinement and homogenization are achieved through repeated high-temperature deformation and austenite recrystallization. Moreover， the high-density dislocations within the deformed layers are effectively reduced by the cyclic tempering heat treatment of single-pass multi-layer additive manufacturing.

Molecular Dynamics Simulation and Parameter Optimization Research for Abrasive Flow Finishing of Additive Manufactured Nozzle Convergent and Divergent Sections

Qian LYU, Weiwei LIU

2025, 36(12):  3017-3022.  DOI: 10.3969/j.issn.1004-132X.2025.12.026

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Aiming at the current difficultes in surface finishing of additively manufactured complex internal flow channels， a multiscale simulation and experimental study of the abrasive flow finishing process was conducted.The abrasive flow velocity under typical pressures was determined through fluid simulation， and the micro-cutting processes were modeled using LAMMPS to establish the relationship between velocity and micro-cutting force. Results indicate that at 60~70 m/s， the cutting force stabilized with moderate magnitude， material removal remaines uniform， and the surface is free of burrs and scratches， defining an ideal finishing condition that provides a theoretical basis for process optimization. Orthogonal experiments with three factors and three levels were carried out on additively manufactured specimens featuring spiral flow channels. Post-finishing results demonstrate effective elimination of typical defects such as powder adhesion， stair-stepping， balling， and support residues， reducing surface roughness Ra from 7 μm to below 0.7 μm and Rp from 21 μm to below 1.25 μm.

Nonlinear Vibration of Friction Stir Welding System of Aluminum Alloys

Shuai MO, Yanchen ZHANG, Yaxin LI, Beibei LI, Sujiao CHEN, Nanjiang PENG, Wei ZHANG

2025, 36(12):  3023-3029.  DOI: 10.3969/j.issn.1004-132X.2025.12.027

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Compared to traditional welding methods， friction stir welding of aluminum alloys produced joints with better quality and smaller residual stress. The study of nonlinear dynamic characteristics helped to optimize the welding processes and enhance welding quality. A nonlinear dynamics model for aluminum alloy friction stir welding systems was established by considering factors such as the flow of thermoplastic materials， time-varying forging forces， and the friction model of plastic metals. The system's differential dynamics equations were solved using the Runge-Kutta method， and the influences of tool rotation speed and feed rate on the system's nonlinear behaviors were described by employing bifurcation diagrams and phase diagrams. The results show that as the tool rotation speed increases， the system sequentially exhibits chaotic behavior and period-doubling bifurcations before stabilizing into periodic motion. As the tool feed rate increases， the system transitions from periodic motion through chaotic and period-doubling states before returning to periodic motion. Additionally， when the feed rate is within the range of 560 to 570 mm/min， the system tends to become unstable instead as the tool rotation speed increases. Proper selection of tool rotation speed and feed rate may prevent system instability and effectively reduce vibration amplitude.

Control of Welding Buckling Distortion in Thin Plates of High-strength Steels AH36 by TTT and Its Mechanism

Bin YI, Yanbin LIU, Ling FU, Dingqi XUE, Zhicheng LIU, Jiangchao WANG

2025, 36(12):  3030-3039.  DOI: 10.3969/j.issn.1004-132X.2025.12.028

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The welding buckling distortion in thin plates of high-strength steels AH36 seriously affected the manufacturing accuracy and was difficult to be completely eliminated by means of correction after welding. TTT was an effective method to control buckling distortion during thin plates welding. A TTT platform was built with induction heating as the auxiliary heat source to conduct conventional welding and TTT experiments in thin plates of high-strength steels AH36 . After the joints were cooled to room temperature， welding distortion was measured by the three-coordinate measuring machine. The maximum relative out-of-plane deformation is as 23.88 mm under conventional welding， and decreases to 13.68 mm under TTT processes. Subsequently， the FE model of butt welded joint was established and thermal elastic plastic FE analyses were carried out for conventional welding and TTT processes. The results are in good agreement with the measured ones. Meanwhile， the maximum relative out-of-plane deformation could be reduced to 4.42 mm with modifying the temperature during TTT processes. Finally， the causes of welding buckling distortion and the control mechanism of TTT during thin plates welding processes with high-strength steels AH36 were clarified based on the welding inherent strain theory. The thermal tensile action formed by the auxiliary heat source changes the constraint degree of the base materials on the weld， which results in less compressive plastic strain during the heating processes and more tensile plastic strain during the cooling processes， so that the inherent strain at the weld is decreased. The tendon force is reduced by 26.4%. The reduction of instantaneous deformation decrease the transverse inherent bending moment by 95.2%， which reduces the initial disturbance resulting in welding buckling distortions， so as to further control the welding buckling distortion of thin plate structures.

Design of Negative Poisson's Ratio Metamaterial Filling Structures for Train Anti-climb Energy Absorbers

Kun HE, Hechao ZHOU, Jimin ZHANG

2025, 36(12):  3040-3046.  DOI: 10.3969/j.issn.1004-132X.2025.12.029

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The existing train anti-climbing energy-absorbing structures had low energy absorption and unpredictable deformation patterns， and were highly susceptible to bending under complex boundary conditions， resulting in a significant decrease in energy absorption and accompanying the risk of climbing and derailment. In order to solve these problems， a negative Poisson's ratio metamaterial was proposed based on an improved topology optimization method and applied to the filling structures of train energy absorbers. Firstly， a negative Poisson's ratio metamaterial was designed by the improved solid isotropic material with penalization， and the samples were prepared by laser selective melting processes， which verified the stable negative Poisson's ratio deformation mode and excellent energy absorption properties， and then the energy absorber filler structures were formed by tensile and periodic arrangement. The specific energy absorption of the proposed negative Poisson's ratio structures is 17.9% higher than that of the conventional honeycomb structures under centric and 40 mm eccentric conditions， and the specific energy absorption degradation rate is significantly lower than that of the conventional structures under eccentric conditions.

Technology on Flexible Polishing for Leading and Trailing Edges of Blisk Blades

Chengshuo LIU, Xiaojun LIN, Bo ZHONG, Wenhui DENG

2025, 36(12):  3047-3056.  DOI: 10.3969/j.issn.1004-132X.2025.12.030

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Aiming at the problems of low polishing efficiency， difficulty in ensuring surface quality and profile accuracy of the leading and trailing edges of aero-engine blades， a study on the automated polishing processes for the leading and trailing edges of blisk blades was conducted. The influence of processing parameters on the size of the polishing contact area at the leading and trailing edges was analyzed， and a predictive model for normal polishing force was established， with a root mean square error of 1.24 N between the predicted and actual values. Based on the Preston equation， the effects of compression amount， spindle speed， sponge abrasive wheel radius， feed rate， and abrasive grit size on material removal in the polishing contact area were modeled. Experiments were conducted using the proposed predictive model for material removal depth at the leading and trailing edges. The experimental results show that the value of surface roughness of the blade leading and trailing edges is reduced to 0.18 μm， verifying that the predictive model may effectively forecast material removal depth. Additionally， the sponge abrasive wheel is proven to effectively improve the surface roughness of the blade leading and trailing edges.

Design of Wheel-mounted Phased Array TFM Imaging and Inspection System for Storage Tank Bottom Plates

Jian LI, Kai ZHANG, Haibin WANG, Zhe WANG, Jingwei CHENG, Chang YAN

2025, 36(12):  3057-3063.  DOI: 10.3969/j.issn.1004-132X.2025.12.031

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To address the issues of high cost， low detection efficiency， and inconsistent quality in routine maintenance operations such as inspection of atmospheric storage tank bottom plates， an ultrasonic phased array inspection system was developed for tank bottom plates. A mechanical scanner was employed to facilitate online， efficient detection of localized corrosion damage， providing technical support for ensuring the long-term safe operation of storage tanks. A wheeled phased array TFM imaging algorithm was proposed， and the inspection accuracy and image quality were enhanced. Experimental results show that， in inspecting a 12 mm carbon steel bottom plate， the system may stably detect artificial flaws on the bottom surface with a depth of 20% of the plate thickness， as specified by the JB/T 10765—2023 standard. The detection sensitivity reaches 5 mm（length） × 0.5 mm（depth） for surface-breaking cracks in welds. And the signal-to-noise ratio of defect images is improved by 10.4 dB compared to conventional methods.