Table of Content

25 June 2025, Volume 36 Issue 06

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A Reliability Allocation Method Considering Distribution and Transmission Models for Mechanical Systems

WANG Zhichao1, LIU Chao1, RAN Yan2, CHEN Yifan3, JIANG Dongxiang1, ZHANG Genbao2, 3

2025, 36(06):  1143-1150.  DOI: 10.3969/j.issn.1004-132X.2025.06.001

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To address the problems of the allocation reliability of lower-level units being greater than that of the upper-level unit in the multi-layer structure reliability allocation of mechanical systems, a novel reliability allocation method was proposed. Firstly, the mechanical systems were divided into a system-function-motion-action(SFMA) hierarchy structure. Then, according to the hierarchy structure consisting of distribution and transmission models, the reliability allocation techniques were proposed by combining the minimum cost method and reliability function, and the reliability allocation models of the mechanical systems, function units, motion units, and sub-motion units were established from top to bottom. Finally, taking the gear grinding machine as an example, the feasibility and effectiveness of the proposed method were verified.

Influences of MCMBs on Electrolytic Dressing and Grinding Performances of Multi-layer Brazed Diamond Grinding Wheels

LIU Wei1, 2, CHANG Jiaqi1, 2, LI Boxin1, 2, YAN Can1, 2, DENG Zhaohui3, WAN Linlin1, 2

2025, 36(06):  1151-1158.  DOI: 10.3969/j.issn.1004-132X.2025.06.002

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The oxide film of large particle size multi-layer brazed diamond grinding wheel had poor quality and insufficient thickness during electrolytic dressing, which led to poor grinding performances. MCMB were added to the abrasive layers to improve this situation. The effects of different MCMB contents on the performances of the grinding wheel and the electrolytic dressing grinding characteristics were investigated. The results show that MCMB may significantly improve the electrolytic film-forming ability of the grinding wheel, the maximum thickness of the oxide film is as 104 μm, and the compactness and adhesion are improved. The ground surface morphology of the test groups containing MCMB has higher integrity and fewer fracture pits. Compared with the test groups without MCMB, the values of surface roughness Ra of the MCMB test groups with a volume fraction of 5% decrease by 29.8% when the workpiece speed is as 40 mm/s and the grinding depth is as 15 μm, and the subsurface damage depth is reduced by 47.9% when the workpiece speed is as 30 mm/s and the grinding depth is as 20 μm.

Grinding and Polishing Mechanism of Hard and Brittle Materials under Cooperation of Fixed and Free Abrasive Grains

LUO Chenyang1, 2, GUO Lei1, 2, CAO Chuqing2, CAO Leilei3, SHI Pengfei1, 2

2025, 36(06):  1159-1169，1177.  DOI: 10.3969/j.issn.1004-132X.2025.06.003

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To investigate the material removal mechanism of hard and brittle materials during elastic grinding and polishing involving fixed and free abrasive grains, a diamond sandpaper grinding and polishing tool integrated with silicone rubber matrix was developed. The elastic tool was paired with varying concentrations of diamond polishing slurry. The contact stress and velocity distributions between the elastic tool and workpiece, as well as the abrasive grain-workpiece contact mechanics were analyzed to establish the material removal models for hard and brittle materials. Subsequently, silicon carbide workpieces were used as test samples, with grinding and polishing pressure, tool speed, and abrasive concentration as processing parameters in single-point experiments, which were conducted to characterize the material removal profile on the machined surfaces. The experimental results reveal that the discrepancies between the established material removal models and the actual material removal depth range from 4.68% to 8.22%. The removal depth is positively correlated with grinding and polishing pressure, tool speed, and abrasive concentration. The established models may accurately predict material removal behaviors in elastic grinding and polishing processes.

Accelerated Load Spectrum Preparation for RV Reducer Service Conditions

YANG Yu1, 2, LI Xiaolei2, TAO Yourui1, 2, GUO Qiyu1, 2, YE Nan1, 2

2025, 36(06):  1170-1177.  DOI: 10.3969/j.issn.1004-132X.2025.06.004

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Aiming at the needs of reliability analysis and life prediction of RV reducers for industrial robot joints, a method of compiling accelerated load spectrum for RV reducers was proposed based on service conditions. On-site collection of industrial robot joint torque-time data and data preprocessing, the Markov chain Monte Carlo methods(MCMC) were applied for time-domain reconstruction and service conditions were synthesized as a typical RV reducer reconstruction of the load history. The rainfall counting methods were used for statistical counting, distribution fitting and parameter estimation, to obtain the statistical distribution laws of the mean-amplitude of the load. The mean-amplitude two-dimensional load spectrum obtained by frequency extrapolation were transformed into 8-level one-dimensional program loading spectrum, and accelerated based on the actual applications of RV reducers, which was compiled into a one-dimensional accelerated program loading spectrum of RV reducers, which greatly shortened the fatigue life test cycle.

Isomorphism Identification Method for Kinematic Chain Based on Exchange and Comparison of Lower Triangular Matrix with Whole Information

ZHANG Guangshuai, SUN Liangbo, LIU Xiaocui, ZHANG Deping, ZHOU Huaxi

2025, 36(06):  1178-1187，1221.  DOI: 10.3969/j.issn.1004-132X.2025.06.005

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 Isomorphism identification was recognized as a critical step in the synthesis processes of kinematic chains(KC). A new MWI was proposed to describe the structural information of KCs. The principles for determining multiple-joint and polygonal links were introduced. Based on the principle that the lower triangular matrix with whole information（LTMWI）may uniquely express the structure of KCs, a new isomorphism identification method was proposed with the comparison and exchange of LTMWI. This method relied on the transformation law of links and key point numbers. Two KCs were expressed by LTMWI, with one LTMWI was selected as the datum matrix. After grouping the key points and moving the non-zero elements of key points in the same group forward, the determined key points and the key points to be determined were obtained. Under the assumption that all key points in the exchange matrix correspond one-to-one with the key point positions in the datum matrix, a finite number of exchange matrices were compared. The method has advantages such as a simple principle, ease of programming, and an identification process requiring only retrieval/comparison operations. It could quickly provide isomorphism identification results, and the mapping of links and even revolute pairs could be obtained. Isomorphism analyses of several KCs demonstrate the aforementioned characteristics of the method.

Modeling and Identification of Robot End-payloads Based on Joint Torque Balance

GAO Guanbin1, 2, ZHAO Siguo1, 2, LI Yingjie1, 2

2025, 36(06):  1188-1197.  DOI: 10.3969/j.issn.1004-132X.2025.06.006

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 To address the challenges of decoupling center of mass parameters in existing end-payload identification methods and the difficulty of implementation on robots with non-open controllers, a torque-balance-based modeling and identification method was proposed for robot end-payloads. The identifiability conditions of the end-payloads were analyzed under joint torque balance, and identification models for the end-payload mass and center of mass position were established. To further decouple the mass and center of mass parameters, a three-step identification strategy was designed, where the load mass was identified first, followed by the center of mass position in x and y, and finally in z. This strategy effectively eliminated the error terms introduced by the projection of joint torques in the identification models. The efficiency of the proposed method was validated through simulation and experiments. Compared with the built-in identification method of a non-open-source six-degree-of-freedom robot, the average error in mass identification is reduced from 0.103 kg to 0.032 kg, while the average error in center of mass position identification is decreased from 50.25 mm to 4.14 mm. Furthermore, compared with dynamics parameter identification, the mass identification error is reduced from 0.179 kg to 0.083 kg, and the center of mass position error is reduced from 10.13 mm to 4.33 mm.

Analysis of Adhesion Characteristics of Novel Negative-pressure Adhesion Wall-climbing Robots

DONG Weiguang1, LIU Aihua2, SONG Yifeng2

2025, 36(06):  1198-1205.  DOI: 10.3969/j.issn.1004-132X.2025.06.007

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Addressing the challenge in optimizing the adhesion performance of wall-climbing robots based on negative pressure adhesion method due to the complexity of internal flow fields and difficulties in precise modeling, a flow field modeling method was proposed based on flow rate conservation. According to the structural characteristics of negative pressure adhesion systems of a wall-climbing robot, mathematical models of airflow field in negative pressure adhesion systems were built by combining the laws of thermodynamics and N-S equations using air flow rate as the related factor. Then, key influencing factors of adhesion performance were identified based on the model: sealing ring width, leakage gap height, and centrifugal pump power. The effective adhesion forces were changing with airflow of adhesion systems. Results of the simulation and prototype experiments show that the models constructed herein may accurately reflect the changing rules of adhesion performance, and may provide evidences for the optimization of adhesion performance of wall climbing robots with negative pressure adhesion method. Finally, according to the movement characteristics of the wall-climbing robots， adsorption performance optimization strategy was increasing the rated adsorption force to self gravity ratio while decreasing the effective adsorption force to self gravity ratio.

Research on Construction Techniques for Wind Power Equipment Contextual Knowledge Graphs

SHI Zhiyuan1, 2, KONG Zhiwei2, CHEN Junzhen3, WANG Shuying3

2025, 36(06):  1206-1213.  DOI: 10.3969/j.issn.1004-132X.2025.06.008

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Traditional methods for constructing knowledge graphs didnt consider the contextual constraints on knowledge, making it challenging to effectively represent the complex associative relationships among vast knowledge in complex electromechanical equipment like wind turbines. This limitation hindered the practical applications of knowledge graphs in the production processes. This paper proposed a method for constructing a context-aware knowledge graph tailored for wind turbine equipment. Initially, the method extracted contextual knowledge, module meta-knowledge, and module instance knowledge generated from project customization. Utilizing the SHACL, an ontology model was constructed, incorporating context paths and attribute value constraints, thereby precisely characterizing and extracting various knowledge types. Furthermore, an ontology parsing-based algorithm is introduced for visualizing contextual knowledge subgraphs. Through the parsing of contextual knowledge classes within the ontology, data observation windows were generated for each contextual class, facilitating the construction of multi-dimensional visualization interactions tailored to specific scenarios. Through practical applications, the proposed method effectively integrates module meta-knowledge with project-specific module instance knowledge, meeting the demands for precise representation and diverse application scenarios in wind turbine equipment knowledge.

Optimization and Experimental Study of Bolt Retreat Groove Rolling Wheels Based on Finite Element Simulation

NIU Yanzhao1, LIU Hongwei1, SONG Yali2, ZHU Xianglong1, HUANG Jiamei2, KANG Renke1

2025, 36(06):  1214-1221.  DOI: 10.3969/j.issn.1004-132X.2025.06.009

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The bolt retreat groove surfaces were susceptible to stress concentration and prone to fatigue failure. To bolster the fatigue resistance of bolts retreat groove surfaces, a specialized rolling tool for the retreat grooves was engineered. The structure of the rolling wheels was optimized based on finite element simulation outcomes of the interaction between the rolling wheel and the bolts retreat grooves. The optimized parameters were utilized to create the rolling tools, and a rolling experiments were carried out. The effectiveness of the rolling wheel parameter optimization was validated by assessing the rolled surface quality, fracture morphology, and fatigue life. The findings indicate that the most favorable residual stress results on the retreat groove surfaces are obtained with a YG8 material rolling wheel with diameter of 60 mm and face angle of 45°. A rolling wheel fillet radius of 0.9 mm produces the deepest residual compressive stress layers, a radius of 1.1 mm yields the highest subsurface residual compressive stress value, and a radius of 1.2 mm generates the maximum surface compressive stress. Trials were conducted with rolling tools featuring three distinct fillet radii, and the extended fatigue life of the bolts is ascertained with a 0.9 mm fillet radius rolling wheels, thereby confirming the optimal configuration of the rolling tools.

Tool Path Planning and Tool Orientation Optimization for Robotic Grinding of Wheel Hub Burrs

GUO Wanjin1, 2, 3, 4, SUN Hao1, LI Qianhui1, TIAN Yuxiang1, CAO Chuqing2, ZHAO Lijun2, 4

2025, 36(06):  1222-1237.  DOI: 10.3969/j.issn.1004-132X.2025.06.010

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 In order to solve the problems of sparse or redundant and uneven distribution of cutter location points, and the difficulty in acquiring the operational tool orientation and drastic changes when the robot was grinding and removing wheel window edge burrs, a robot grinding path planning method with cutter location point planning and tool orientation acquisition and optimization for wheel window burrs were proposed. The wheel window edge curve was described by using NURBS curve morphology feature parameters and robotic cutter location point planning was conducted for the wheel window edge a method for acquiring the normal vector of the inner face of the wheel window was proposed considering the wheel point cloud and window surface features, and a local coordinate system at the tool position points was established to describe the robot tool orientation. A robot end tool orientation optimization model was established and optimally solved to obtain a continuous smooth robot end tool orientation for the wheel window. Wheel window edge burr robot grinding experiments were conducted to verify the effectiveness of the proposed robot grinding path planning method for wheel window burrs. The results show that the robot joint angle curve is relatively smooth in the wheel window burr grinding and removing processes, and the robot may accurately reach the planned cutter location points and the end tool contacts window edges well and maintains the appropriate operational orientation. The maximum chamfer of different wheel window edges after burrs grinding remains below 1.50 mm, and the maximum average value of chamfer measurements at different positions is as 0.64 mm, which is within the specified range of the processing specification.

Multicollinearity Parameter Feature Selection for Manufacturing Processes Based on LLEs

HU Sheng1, 2, GAO Bingbing1, ZHANG Xi1, LIU Dengji1

2025, 36(06):  1238-1246.  DOI: 10.3969/j.issn.1004-132X.2025.06.011

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In manufacturing processes, a large number of parameters were easily caused to have multicollinearity, which led to problems such as inaccurate prediction of quality indicators. To address these problems, a feature selection method for multicollinear parameters in the manufacturing processes was proposed based on LLE. Firstly, the multicollinearity of the manufacturing process parameters was diagnosed, and then the multicollinearity was eliminated by using the least absolute shrinkage and selection operator(LASSO) regression. Secondly, the LLE algorithm was used to perform feature selection on the parameters after LASSO regression to obtain independent feature spaces, and they were input into the whale optimization algorithm-support vector machine(WOA-SVM) model to verify the parameter feature selection effectiveness of the proposed algorithm. Finally, the effectiveness of the proposed method was verified through case analysis. The results show that compared with the original data, the proposed method may obtain more accurate prediction results under a lower-dimensional feature space, the correlation coefficient value is up to 0.9702, and the accuracy of feature selection increases by 24.989%.

Modelling and Optimisation of Dynamic Scheduling in Chinese Materia Medica Pharmaceuticals Workshops Based on Multiple Motivation Drivers

ZHAO Peirui1, DENG Chao1, ZHU Bo1, YAN Wenbin1, LIANG Min2, CHEN Min2

2025, 36(06):  1247-1260，1299.  DOI: 10.3969/j.issn.1004-132X.2025.06.012

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A dynamic scheduling problem of Chinese materia medica pharmaceutical workshop driven by multiple dynamic factors(DSP-CMMPW-MDF) model was established, the multiple dynamic factors such as raw material shortages, emergency order insertions, and machine breakdowns. An improved artificial bee colony with Q-learning(IABC-QL) algorithm was proposed to solve the DSP-CMMPW-MDF with the optimization objective of minimizing makespan. In the IABC-QL algorithm, an opposition-based learning strategy was proposed to generate the initial population, ensuring high quality and diversity of the population individuals. Five local search operations were designed to enhance the deep exploration capability of the algorithm. Thus the proposed model and algorithm were applied to a Chinese materia medica pharmaceutical granule production workshop. The results show that the proposed model may effectively improve the flexibility and adaptability of the production systems in the face of uncertainties. Additionally, a comparison with existing algorithms validates the effectiveness of the proposed algorithm.

Thin-walled Workpiece Milling Deformation Error Prediction Based on Multi-source Information Fusion and Ensemble Learning

YIN Jia1, ZHENG Jian2, LIU Yao3, JIA Baoguo1, DUAN Xiaorui1

2025, 36(06):  1261-1268.  DOI: 10.3969/j.issn.1004-132X.2025.06.013

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In practical machining processes, the dimensional accuracy of thin-walled workpiece was significantly affected by multiple factors including cutting forces, forced vibrations, chatter phenomena, geometric characteristics of workpiece and material properties, rendering deformation prediction and control particularly challenging. A multi-source information fusion method for deformation error prediction in thin-walled workpiece milling processes was developed. Machining parameters, vibration signals, and other relevant data were integrated to establish a deformation error prediction model through Stacking ensemble learning methodology, with comprehensive experimental validation performed. Comparative analyses reveal that the constructed model demonstrates superior robustness, higher accuracy, and enhanced practicality when compared with conventional data-driven prediction methods.

DIA Method for Multi-part Stacked Structure Devices Based on Disassembly Information Extraction

WANG Yunfan1, 2, ZHU Libin1, 2, CUI Chuangchuang1, 2, HUANG Haihong1, 2

2025, 36(06):  1269-1279.  DOI: 10.3969/j.issn.1004-132X.2025.06.014

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Aiming at the problems of low efficiency and accuracy of disassembly interference detection due to the multi-part stacked structure devices, a DIA method was proposed based on DIE to improve the accuracy of disassembly information acquisition and shorten the disassembly time of parts. The disassembly information in the design model was extracted and quantified as a priority matrix through two-stage interference detection involving the boundary box and solid intersection. The dynamically changing disassembly information was accurately extracted by combining the dual coordinate system transformation of the assembly and parts. In order to verify the feasibility and effectiveness of this method, CAD design model experiments were conducted. The priority matrix generated by DIA and traditional interference detection methods were obtained and used as structural constraint information, which were input into the BOA-GA to search for the optimal disassembly sequence. The experimental results demonstrate that the accuracy of the priority matrix generated by DIA is increased by 28.57% compared with the traditional method, and the disassembly time of the optimal sequence is shortened by 3.31%.

Processing Parameter Energy-saving Optimization for Boring Automobile Engine Crankshaft Holes Considering Coaxiality

ZHANG Dengyong, LI Congbo, WU Shaoqing, ZHANG You, LI Chengyuan

2025, 36(06):  1280-1289.  DOI: 10.3969/j.issn.1004-132X.2025.06.015

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To address the issues of the coaxiality value of the automobile engine crankshaft holes was too large or even out of tolerance after boring, and the low energy efficiency of boring processes, a study of processing parameter energy-saving optimization for boring automobile engine crankshaft holes was conducted considering coaxiality. The influencing factors of coaxiality in boring crankshaft holes were analyzed and the coaxiality value prediction models were established based on the finite element methods and support vector machine regression algorithms. Then, the energy consumption characteristics of boring crankshaft holes were analyzed, and a boring parameter optimization model was established aiming at specific energy and maximum coaxiality value. The improved multi-objective dragonfly algorithm was used to solve the model and the optimal combination of processing parameters to balance energy efficiency and coaxiality was determined. Finally, the case study indicates that after the optimization, the maximum coaxiality value is reduced by 10.81%, and the specific energy is reduced by 4.61%, which verifies the effectiveness of the optimization model.

Energy-saving Design of Aerial Work Platform Flying Boom Hydraulic Systems Based on Cylinder Diameter and Flow Matching

LIU Yuchao1, XI Yi1, ZHANG Yuxiao2, DAI Juchuan1, HE Lejun1, XIA Huqiang2

2025, 36(06):  1290-1299.  DOI: 10.3969/j.issn.1004-132X.2025.06.016

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Aiming at the problems of very low efficiency of the aerial working platform flying arm hydraulic systems, a new method was proposed to reduce the energy consumption of the hydraulic systems by matching the hydraulic cylinder bores of the flying arms and the output flow rates of the pump. A mathematical model of the load apllied on the flying arm mechanisms was established, and the simulation model of the aerial working platform flying arm hydraulic systems was established by AMESim software, and the energy consumptions of each design scheme were calculated on the basis of verifying the accuracy of the simulation model through experiments. The results show that: under the premise of ensuring that the actuator load and output speed of the flying arm hydraulic systems are unchanged, by matching the hydraulic cylinder bores of the flying arms and the flow rates of the pump, and the load-sensitive pump is avoided to work in the small-displacement areas. The efficiency of the hydraulic systems may be effectively improved, and the overall efficiency of the optimized flying arm hydraulic systems is improved by 4.6%.

Development Trends and Prospects of Additive Manufacturing Technology for Cemented Carbide Cutting Tools

JIANG Feng1, 2, HU Ronghui1, DENG Jiedong1, ZHANG Tian1, HUANG Guoqin1, 2, XU Yangli1, 2, LI Yousheng3, LIU Chao4

2025, 36(06):  1300-1313.  DOI: 10.3969/j.issn.1004-132X.2025.06.017

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Two technical routes for the additive manufacturing of cemented carbide cutting tools were reviewed: the powder bed fusion  route based on thermal forming, and the forming-debinding-sintering based on cold printing of  green bodies, followed by debinding and sintering. The powder bed fusion technique might produce cemented carbide cutting tools with near-theoretical density, but issues such as porosity, cracking, decarburization and cobalt evaporation remained. By adjusting parameters such as laser energy density, scanning speed, and powder characteristics, the quality of the printed components might be significantly improved. The forming-debinding-sintering technique might produce cutting tools with excellent surface quality and superior mechanics properties, but challenges such as binder residue and component shrinkage persisted. By optimizing key parameters such as binder type, debinding process, and sintering temperature, the density and mechanics properties of the components might be enhanced. Additionally, heat treatment processes such as vacuum sintering, hot pressing, and hot isostatic pressing might further eliminate internal defects in the materials, thereby improving the overall performance of the cutting tools. 

Effects of Solution Treatment on Microstructure and Mechanics Properties of TC4 Titanium Alloy Parts Formed by Forging/Additive Manufacturing Composite Forming

WANG Yahui1, 2, 3, HUANG Liang1, 2, LIU Xiang1, 2

2025, 36(06):  1314-1321.  DOI: 10.3969/j.issn.1004-132X.2025.06.018

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Laser solid forming(LSF) technology was used to perform compound forming on the forged TC4 titanium alloy substrates. The microstructure evolution of LSF additive manufacturing areas and the joint parts of forged substrates under different solid solution heat treatment conditions and the properties of TC4 titanium alloy were studied. The results show that under the conditions of furnace cooling or air cooling, the higher the solution heat treatment temperature, the α / α ' phase at the joints of composite forming gradually grows and coarsens. Under the condition of solution treatment at 1040 ℃, the original obvious joint zones are transformed into a homogeneous α-colony structure. With the increase of solution temperature, the yield strength and tensile strength of the composite parts decrease. The cooling mode of solution treatment has effects on the microstructure of the joint zones，the width of α phase under air cooling conditions is smaller than that under furnace cooling conditions. Under the conditions of furnace cooling, the higher the solution temperature the lower the hardness of the joint zones, and the microhardness near the joint zones is higher than that far away from the joint zones.

Prediction of Cracks and Optimization of Processing Parameters in Laser Cladding of Ni60 Based on HGA-ACO-RFA

LI Tao, DENG Linhui, MO Bin, SHI Feifan, LIU Weiwei

2025, 36(06):  1322-1328,1337.  DOI: 10.3969/j.issn.1004-132X.2025.06.019

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To explore the complex nonlinear mapping relationship between the cracks in the cladding layer and the processing parameters during laser cladding of Ni60, the entropy method combined with TOPSIS comprehensive evaluation method was used to comprehensively characterize and evaluate the cracks in the cladding layers. The HGA-ACO was used to optimize the hyperparameters of the RFA, and a prediction model between processing parameters and crack evaluation indicators was constructed. Finally, the genetic algorithm was used for reverse optimization of processing parameters. Results show that compared with the ACO-RFA model, HGA-ACO-RFA significantly improves prediction accuracy and evaluation indicators, and the optimal processing parameters obtained through reverse optimization may prepare almost crack free cladding layers.

Effects of Glass Fiber Mass Fraction on W-PACIM Pipes of Long Glass Fiber Reinforced Polypropylene

LIAO Qiansheng1, 3, LIU Hesheng2, KUANG Tangqing2, LIU Jiahao2, ZHANG Wei2

2025, 36(06):  1329-1337.  DOI: 10.3969/j.issn.1004-132X.2025.06.020

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To study the effects of glass fiber mass fraction on W-PACIM pipes with long glass fiber reinforced polypropylene as the outer material and pure polypropylene as the inner material, the influences of glass fiber mass fraction on the residual wall thickness, the orientation distribution of glass fibers and the pressure resistance of the pipes were analyzed by experimental methods. The results show that with the increases of glass fiber mass fraction, the total residual wall thickness of the pipes decreases first and then increases. The outer layer of the pipes may be divided into near the mold wall layer, the middle layer and the near interface layer according to the distribution characteristics of the glass fiber orientations, the orientation of the glass fiber along the melt flow direction increases gradually from the outside to the inside, the uniformity of the distribution of the outer glass fiber decreases with the increase of glass fiber mass fraction. The pressure resistance of pipes increases first and then decreases, when the glass fiber mass fraction is 20%, the pressure resistance of pipes is the best.

Study on Thickness Distribution of Single Point Incremental Hydroforming of Complex Shaped Parts

SHANG Miao, LI Yan, SHAN Shunkun, YANG Mingshun

2025, 36(06):  1338-1344.  DOI: 10.3969/j.issn.1004-132X.2025.06.021

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To analyze and enhance the performances of single point incremental forming for complex shaped parts, a new process combining SPIF and hydroforming was presented for manufacturing multi-featured parts with spire structures. The forming processes of the target parts were designed, the theoretical prediction model of thickness was established, and the effects of different hydraulic parameters on the thickness distribution of the target parts in different forming stages were analyzed. The experimental results show that complex shaped parts may be formed using the new processes and appropriate hydraulic pressures; the geometric errors between the experimental and theoretical profiles may be reduced from 11.44% to 5.18% with assistance compared to SPIF without hydraulic assistance; the thickness distribution patterns are related to the assisted pressure, forming heights, forming shape, etc., and the established theoretical model may be used to predict the thickness distribution of complex shaped parts.

C-warping Mechanism and Treatment Strategies in Leveling Processes of Strip Steels

YANG Yonghui1, ZHANG Ji1, TAN Hailong1, NIU Baicao1, BAI Zhenhua1, 2, 3

2025, 36(06):  1345-1351.  DOI: 10.3969/j.issn.1004-132X.2025.06.022

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 In order to solve the problems of C-warping defects in strip steels in the leveling processes, the processing parameters in the strip leveling processes were optimized, and a set of C-warping prediction and treatment strategies for strip steels were developed. The formation mechanism of C-warping was analyzed from three aspects: rolling, processing lubrication systems and the influences of anti-wrinkle rollers and anti-trembling rollers on the forces of strip steels. The stress distribution of the horizontal direction of the outlet strips in the thickness was obtained, based on the stress analysis of the strips under the assumption of half-plane infinite body， the maximum and minimum transverse elongation in the thickness direction of the strips were obtained, and the height of the C warp of the strips was obtained through the geometric relationship. A set of optimal height settings of anti-wrinkle rollers and anti-trembling rollers were sought to minimize the objective function of the comprehensive control, and the elongation in the direction of strip thickness was controlled, so as to reduce C-warp. The model and treatment strategies were applied to a leveling unit in China, and the prediction errors of C warping height are controlled within 10%, and the maximum warpage ranges of the unit are reduced from 1.4~6.5 mm to 0.9~4.5 mm. The results show that the C warpage prediction and treatment strategy meet the production demands, and the warpage values are significantly reduced, which reduces the repair rate caused by warpages.

Design and Numerical Simulation and Experiments of Gas Supply Backpacks for Positive Pressure Protective Clothing

HOU Yulei1, LI Ximeng1, SUO Huai2, LI Yue1, ZENG Daxing3

2025, 36(06):  1352-1362，1370.  DOI: 10.3969/j.issn.1004-132X.2025.06.023

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At present, the function of positive pressure protective clothing is relatively single, the high internal temperature and difficult pressure control resulted in low safety and comfort. Therefore, a supporting device integrating supply/exhaust, filtration and cooling functions was proposed. The data required to maintain a slightly positive pressure state within the protective clothing was tested, and the structure of the air-supply backpack was designed in modules. A heat transfer analysis was conducted on the semiconductor refrigeration module, and a simulation model was established to analyze the impacts of profile dimensions on refrigeration performance based on CFD (computational fluid dynamics). The parameters of temperature and pressure were stabilized by fuzzy PID control, the transfer function was solved, the controller was designed and verified by Simulink simulation. The FLUENT simulation model of micro positive pressure protective clothing was built to analyze the distribution law of flow field and temperature field in protective clothing and the influences of air supply temperature. The prototype of air supply backpacks was developed and the temperature and humidity of protective clothing were tested. The results show that the air supply backpacks may dehumidify to normal ambient humidity within 30 s and reduce 5 ℃ compared with room temperature within 100 s.

Adaptive Control Method of AMB Based on Characteristic Model and Tracking Differentiator

JI Li, CHEN Meihao

2025, 36(06):  1363-1370.  DOI: 10.3969/j.issn.1004-132X.2025.06.024

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In order to improve the robustness of AMB systems in the face of noise interference and external shocks, an adaptive control method was proposed based on characteristic model and tracking differentiator. The characteristic model parameters of AMB systems were identified online through the input and output data of the control system, and the golden section adaptive controller was designed based on the identified characteristic model. The range of characteristic parameters of AMB systems was derived, the projection gradient method with nonlinear saturation function was used to identify the parameters of the systems, and the tracking differentiator was used to track and filter the measurement data of the control system, which further improved the robustness of AMB systems in the face of noise interference. The proposed control method was tested on the test platform of high-speed magnetic levitation motor. The experimental results show that the tracking differentiator may effectively filter out the interference of external noises on the measured data. Compared with the commonly used incomplete differential PID control method, the proposed adaptive control method may effectively improve the control accuracy and robustness of AMB systems, and the vibration peak values of the magnetic suspension rotor are reduced by 51.4%. 

Simulation of Dynamic Characteristics of Excavator Working Processes and Multi-objective Optimization Design Method of Main Component Parameters

LIN Shuwen, LU Zhe, WEI Shijia, CHEN Jianxiong, GU Tianqi, XIE Yu

2025, 36(06):  1371-1379.  DOI: 10.3969/j.issn.1004-132X.2025.06.025

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To address the issues that the existing excavator component parameter optimization design could not ensure optimal performance across various positions and conditions throughout the excavation operations, and did not consider the energy consumption characteristics of the operational processes, a new multi-objective optimization design method of excavator work device parameters with the target of the power and energy consumption characteristics of the whole typical working condition operational processes was studied. Through the dynamics simulation of the ADAMS-based parametric excavator virtual prototype, the drive force and power characteristics of the hydraulic cylinders in four typical operating conditions were analyzed, the optimization conditions of work devices were determined, and a new multi-objective optimization model was established which considering the drive force transmission ratio and power characteristics of the hydraulic cylinders in the typical operating conditions. The parameters of the bucket, stick and boom were optimized in a sequential multi-objective process in combination with the parametric virtual prototype of a complete excavator work device. The optimization results demonstrate the effectiveness of the new multi-objective optimization method by improving the performance of the work device in transmitting power during excavator operations while reducing the energy consumption of the hydraulic cylinders.

Research on Hybrid Power Energy Management Strategy Based on Sequential Real-time Decision Making with Hybrid Model Predictive Control

SUN Xiaojun1, LIU Conghao1, ZHANG Qiao1, SONG Enzhe2

2025, 36(06):  1380-1393.  DOI: 10.3969/j.issn.1004-132X.2025.06.026

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An optimization strategy and evaluation framework for power distribution in marine hybrid propulsion systems was developed. Experimental data and component characteristics were analyzed, and system identification and clustering algorithms were employed to integrate continuous and discrete variables effectively. A state-space equation was formulated to represent the hybrid characteristics of the propulsion systems. A trade-off performance index function was defined to balance fuel consumption reduction and power performance enhancement. Based on a mixed logical dynamic model, a hybrid model predictive controller（HMPC） was designed to optimize the collaborative operations of natural gas engines, permanent magnet synchronous motors and clutches. Finally, the proposed HMPC was tested in real machine in terms of energy saving and power improvement using test conditions. The results show that the fuel-optimal HMPC saves 2.72% fuel and the power-optimal HMPC improves power performance by 59.72% compared to the HMPC that combines economy and power.