制造技术与机床

Robot constant force grinding based on variable parameter impedance control

ZHENG Shuai, GUO Kai, SUN Jie

2024, (3): 9-15. doi: 10.19287/j.mtmt.1005-2402.2024.03.001

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Abstract:
An adaptive impedance control algorithm with online adjustment and offline optimization of impedance parameters was designed for the constant force polishing needs of robots to achieve polishing force control. The adaptive impedance control algorithm takes stiffness parameters as time-varying parameters and adjusts them online in real-time based on the grinding contact force to eliminate steady-state errors during the grinding process. Aiming at the problem of difficult tuning of damping and inertia parameters, an improved particle swarm optimization algorithm is adopted for offline optimization of impedance parameters to reduce system overshoot and adjustment time. A constant force polishing simulation of the robot was conducted, and the simulation results showed that the method proposed in this paper can comprehensively improve the constant force control performance of the robot. The robot constant force polishing experiment was conducted, and the experimental results showed that the method proposed in this paper can effectively improve the surface quality of robot polishing.

Research on trajectory planning method of 4+2 degree-of-freedom robot dedicated to blade grinding

REN Lijuan, CHEN Ke, YAN Weijian, LI Kun, YANG Zhijian, ZHANG Guangpeng

2024, (3): 16-21. doi: 10.19287/j.mtmt.1005-2402.2024.03.002

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As the last process of precision machining of complex curved blades, the processing quality of abrasive belt grinding directly affects the service performance and life of the blades. The traditional six-degree-of-freedom robot with multi-joint tandem connection has obvious weak rigidity, and its deformation resistance is not good when clamping large blades at the end. For this reason, a 4+2 degree of freedom blade grinding robot system is designed and developed. Research of complex surface blade grinding trajectory planning method is carried out with the self-developed grinding robot system. First of all, the kinematics model of the robot is established based on the D-H method. The forward and inverse solutions of robot kinematics are given. A trajectory planning method is proposed that comprehensively considers the interference between polishing tools and workpiece curvature, the influence of tool path spacing and trajectory point density on residual height. A collaborative motion model of two units is established to ensure the machining implementation of the blades. Finally, the correctness of the obtained grinding trajectory is verified through numerical control program simulation of the blade polishing trajectory.

Kinematics simulation experiment of towed welding robot in Matlab environment

CAI Yang, YU Gongzhi

2024, (3): 22-30. doi: 10.19287/j.mtmt.1005-2402.2024.03.003

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The D-H parameters of an ER series towed welding robot were determined by MDH (modified Denavit-Hartenberg) method, and the corresponding joint coordinate system and DH model were created. The kinematics analysis is solved based on Tool-box 10.4 in Matlab software. The linear multiplication of the homogeneous transformation matrix is used to deduce the forward solution of the kinematics, and the closed solution of the inverse kinematics equation is solved by Newton-Raphson method, which verifies the rationality of the kinematics modeling of the robot. The trajectory planning is completed in Matlab, and the motion trajectory is programmed with cubic and quintic interpolation methods in joint space respectively. The work space analysis of the robot arm under global and limited conditions is completed, and the overall simulation results fully prove that the motion performance of the towed welding robot is reasonable and stable. This scheme lays a theoretical foundation for further experiments and research and development, and has practical application significance for the same series or configuration of robotic arms.

Evolution of surface and subsurface properties of coated tools in high speedcutting of GH2132

YANG Wenfeng, ZHENG Guangming, GAO Jun, LIU Tao, DU Honggang

2024, (3): 31-35. doi: 10.19287/j.mtmt.1005-2402.2024.03.004

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During high-speed cutting, the changes in surface properties and subsurface stresses of coated cutting tools directly affect their cutting performance. High speed turning experiments were conducted on GH2132 high-temperature alloy using PVD-TiAlN hard alloy coated tools to study the changes in tool surface properties during the cutting process. Raman spectroscopy was used to measure the residual stress distribution on the sub surface of coated tools at different wear stages. The results show that during the complete service life of the cutting tool, the residual compressive stress and surface microhardness both show a trend of first increasing and then decreasing. The residual stress in the coating is mainly residual compressive stress, which gradually increases along the depth direction. However, when the wear reaches the later stage of stable wear, the residual compressive stress of the coating decreases near the substrate. During high-speed dry cutting, the tool has the best surface performance and the maximum residual compressive stress on the subsurface during the early stage of stable wear. At this time, the tool has the best cutting performance and slow tool wear.

Research on the effect of milling process on surface quality of laser claddingadditive Fe45 alloy

ZHOU Jun, SHU Linsen, WANG Jiasheng

2024, (3): 36-43. doi: 10.19287/j.mtmt.1005-2402.2024.03.005

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To address the problems of poor surface quality of laser cladding additive remanufactured Fe45 alloy, the laser cladding layer can not meet the function and assembly requirements of precision machinery parts.The influence of the milling process on milling force, surface roughness and micromorphologies were studied.The milling subtractive test was carried out by orthogonal test method.The effects of spindle speed (S), feed speed (F) and cutting depth (a_p) on milling force and surface roughness of additive parts were evaluated by variance and range analysis.The influence of milling subtractive process on surface morphology and chip is analyzed from the microscopic point of view.The results show that the milling parameters have a great influence on the surface quality, and the most significant effect on the milling force is the milling depth, and the most significant effect on the surface roughness is the feed speed.The surface roughness Ra of Fe45 laser additive can be reduced from 13.68 μm to 1.7 μm after milling, which is 87.6% lower. From the experiment, it can be seen that the milling reduction process can significantly improve the surface quality of laser cladding additive remanufacturing Fe45 alloy, which has guiding significance for the mechanical processing of laser cladding coatings.

Study on the influence of cutting parameters of high-strength steel on cutting force of high-efficiency turning

SU Ping, HUANG Shutao, SHI Haicheng, ZHUANG Zhong, XU Lifu, ZHANG Yupu

2024, (3): 44-50. doi: 10.19287/j.mtmt.1005-2402.2024.03.006

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D6AC high-strength steel has high strength and good toughness, and is a difficult-to-process material widely used in many fields. In this paper, from the perspective of achieving efficient cutting of D6AC high-strength steel roughing, the orthogonal test method is used to study the significance of the three elements of the cutting amount on the cutting force during its efficient turning processing, and the order of significance of each cutting amount on the cutting force is obtained by using extreme difference analysis and grey correlation analysis according to the test results, and the empirical formula of each cutting component force and cutting combined force is established and tested. The results show that the empirical formulae for cutting forces have good accuracy.

Optimization of free surface measurement path based on improved differential evolution algorithm

WANG Guanzhong, WANG Shijun, RAN Chuandong

2024, (3): 51-56. doi: 10.19287/j.mtmt.1005-2402.2024.03.007

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To address the issues of slow convergence and susceptibility to local optima in traditional differential evolution algorithms, as well as the poor optimization stability caused by the randomness in individual selection, a multi-restart strategy is introduced in this paper. The algorithm is executed multiple times with different random seeds, increasing the algorithm’s spatial exploratory capability and, to a certain extent, resolving the problem of easily falling into local optima. Through the incorporation of a new mutation strategy, the optimization stability is improved by approximately 10%. Additionally, a parameter self-adaptive tuning mechanism is introduced, dynamically adjusting the algorithm’s parameter values, resulting in an approximately 10% increase in convergence speed and enhancing the algorithm’s robustness.

Development of DSP bootloader for MBD code download based on CAN communication

GUO Yifeng, GUO Shicheng, HUANG Limin, ZHANG Li

2024, (3): 57-63, 68. doi: 10.19287/j.mtmt.1005-2402.2024.03.008

[Abstract] FullText HTML PDF(4316KB)

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In order to meet the demand for convenient downloading of MBD (Model-Based Design) code in practical applications of DSP embedded systems, this study designs a Bootloader solution based on CAN communication for MBD code download. Taking TMS320F28335 as an example, by analyzing the structure of MBD code, a memory partition scheme between Boot program and MBD program is designed to ensure the effectiveness and stability of program download. The corresponding Boot program and host computer program are developed, and the implementation process of Bootloader is introduced in detail. The functions of Committed step are analyzed and explained, and the program download is realized using CAN communication. The experimental results indicate that this method is stable, reliable, and practical, providing a feasible and efficient solution for downloading MBD code in practical applications in DSP embedded systems.

Steady rests design in crank axle of spindle neck lathe and material rack topology optimization

HUO Hongxu, YU Xin

2024, (3): 64-68. doi: 10.19287/j.mtmt.1005-2402.2024.03.009

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Abstract:
Aiming at the rippling on CNC lathe boring that inspecting step by step and confirming the rippling source preliminarily. Applying the float chuck fixture to improve the spindle rigidity and decrease the depth of the lathe tool indirectly which approve the rippling and spindle irrelevantly. Applying the envelope demodulation analysis method, by apply the LC-810 vibration signal acquisition analyzer to pick the vibration signal on front-end and back-end of spindle, the average data at 22.37 Hz and 45.94 Hz, which approach to the 22.127 Hz and 44.792 Hz of NN3048 and NU1038 bearing fault character frequency. Through the dismantle bearing and boring test that testify envelope demodulation analysis method is available on bearing fault diagnose. The result is the abrasion between NN3048 bearing and NU1038 outer race is the source of rippling, the theory and test result is consistent.

Research progress of diamond wire saw electrical discharge composite sawing of hard-brittle semiconductors

ZHANG Naijun, GAO Yufei, GUO Zhitian

2024, (3): 69-75. doi: 10.19287/j.mtmt.1005-2402.2024.03.010

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The rapid development of the solar photovoltaic and the electronics industry has put forward higher requirements for the cutting of hard-brittle semiconductor materials such as crystalline silicon. To further improve the cutting quality and production efficiency of hard and brittle semiconductors and reduce the production cost, diamond wire saw electrical discharge composite sawing has been applied to hard and brittle semiconductor cutting. In this paper, the research progress of this composite sawing technology of hard and brittle semiconductor materials is reviewed from the processing principle, process performance and influencing factors, and the future development and research direction are prospected.

Research status of deformation damage behavior of high strength metastable β titanium alloys

ZHU Chenzhe, FU Xiuli, WANG Liqun, YUAN Peiqi, MEN Xiuhua

2024, (3): 76-84. doi: 10.19287/j.mtmt.1005-2402.2024.03.011

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Abstract:
Metastable β titanium alloy has mechanical and physical properties such as low density, high specific strength, good plasticity and excellent corrosion resistance, and has been widely used in aerospace, biomedicine, petrochemical and other fields. In order to realize the development and application of a new generation of high-strength and high-plastic titanium alloys, the relationship between the mechanical properties of metastable β titanium alloys and their deformation damage behavior must be clarified. In this paper, the microstructure evolution of metastable β titanium alloys in the process of deformation damage is analyzed, the various deformation behaviors of metastable β titanium alloys and the relationship between each deformation are summarized, and the improvement of the mechanical properties of metastable β alloys under the influence of different deformation behaviors is summarized. Then, the damage behavior and internal microstructure evolution of metastable β titanium alloys under dynamic load are expounded, and the relationship between microscopic damage and alloy strengthening and failure is discussed, in order to put forward new insights into the development and optimization of new titanium alloys.

Pelican optimization algorithm improved based on hybrid strategy

SU Yingying, REN Mantong

2024, (3): 85-93. doi: 10.19287/j.mtmt.1005-2402.2024.03.012

[Abstract] FullText HTML PDF(1408KB)

Abstract:
Aiming at the problems of low solving accuracy, insufficient stability, and easy to fall into local optimization of the pelican optimization algorithm, a improved pelican optimization algorithm (IPOA) with improved hybrid strategy is proposed. Firstly, in order to enhance the randomness and diversity of the population, expand the search range of the population, introduce the back-refraction learning mechanism. Secondly, the fusion of sine-cosine algorithm and pelican algorithm is used to improve the way of pelican search for prey, and enhance the local search and global search capabilities of the algorithm. Then, the Levy flight mechanism is used to update the position of the pelican, so as to improve the search ability of the algorithm to find the optimal value. Finally, an adaptive t-distribution variation operator is introduced, and the number of iterations of the algorithm is used as the degree-of-freedom parameter of the t-distribution to enhance the diversity of pelican populations and avoid the algorithm falling into local optimum. The improved algorithm is compared with the seagull optimization algorithm, chimpanzee optimization algorithm, whale optimization algorithm, snake swarm optimization algorithm, and basic pelican optimization algorithm through 12 standard test functions, and the results show that IPOA has better convergence speed and stability. Finally, the improved Pelican algorithm is applied to the pressure vessel design optimization problem, which further proves that the improved algorithm has good solution performance.

Optimisation of the column structure of a small drilling machine based on reverse engineering

WANG Dongcheng, WANG Yu, LIU Shulian, CHEN Suifan

2024, (3): 94-101. doi: 10.19287/j.mtmt.1005-2402.2024.03.013

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The structural performance of the column is the key to the stability of the machine tool. In order to improve the dynamic and static characteristics of the column while reducing its mass, we start from the acquisition of the machine structure model, collect the point cloud data of the machine parts through 3D scanning, and then convert it into a solid model by using the inverse modelling technology, and then use the finite element simulation to solve the key indexes of the column and complete the optimization. In terms of model acquisition, 2D analysis is used to compare the deviation between the solid profile of the column and the point cloud data, and the overall average deviation is measured to be −0.050 9 mm, which meets the test requirements. In terms of structural optimisation, multi-objective topology optimisation is used to quickly determine the overall layout of the column structure, and further dimensional optimisation is used to reduce the impact of increased total deformation on the machining accuracy of the machine. Under the condition that the total deformation is basically unchanged, the 1st-order intrinsic frequency of the column is effectively increased by 16%, and the mass is reduced by 5.3%. This method integrates the use of reverse engineering and finite element simulation, provides model parameters obtained in reverse for finite element analysis, increases the engineering reliability of structural optimisation, provides new ideas for product improvement and redesign, accelerates the efficiency of new product development, and saves design and manufacturing costs.

Semi-automatic electromagnetic riveting actuator development and riveting verification of aerospace conical parts

DANG Chenglong, ZHANG Minghao

2024, (3): 102-107. doi: 10.19287/j.mtmt.1005-2402.2024.03.014

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A semi-automated electromagnetic riveting technology was proposed to achieve high-quality and long-life connections for the typical riveting characteristics of aerospace conical cylindrical structural components; The semi-automatic electromagnetic riveting actuator system that including axis adjustment mechanism, buffer mechanism, guide mechanism and brake mechanism was designed. The impact recoil calculation test was completed and the recoil characteristics of electromagnetic riveting was analyzed. It is found that the recoil impulse of electromagnetic riveting is slightly less than 30 N·s under 1 000 V, which can provide support for the precise design of electromagnetic riveting buffer mechanisms. The comparative test on the riveting strength of ordinary pneumatic riveting and electromagnetic riveting was completed, which verifies the feasibility of semi-automatic electromagnetic riveter to solve the problem of high-quality and long-life connection of conical cylindrical structures.

Study on the effect of nano SiC on the properties of friction stir welded joints of magnesium alloy

GAO Hui, ZHANG Kai, LIN Yuanhao, LEI Dan

2024, (3): 108-114. doi: 10.19287/j.mtmt.1005-2402.2024.03.015

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Abstract:
In order to improve the comprehensive performance of AZ31 magnesium alloy welded joints, the friction stir welded joints without nano-SiC-1 pass and with nano-SiC-1 pass and 4 passes were studied respectively. The microstructure and mechanical properties of the welded joints were analyzed by optical microscope, microhardness tester and tensile testing machine. The corrosion behavior of the joints was studied by electrochemical workstation. The corrosion morphology, element composition and phase composition of the joints were analyzed by scanning electron microscopy, EDS and XRD. The results show that the friction stir welding joint is well formed and has no defects. The microstructure of the weld nugget zone of the joint is uniform equiaxed grains. The increase of welding passes can effectively improve the distribution of SiC particles. The existence of heterogeneous nucleation sites plays a role in grain refinement and improves the mechanical properties of the joint. In the 3.5% NaCl solution corrosion test, the corrosion resistance of the joint containing SiC particles is improved, and the corrosion resistance of the SiC-4 pass joint is the best.

Analysis and research on static and dynamic characteristics of highspeed motorized spindle based on NewSpilad

DAI Yuhong, HOU Yaru, REN Huiling, ZHU Xiaofeng

2024, (3): 115-119. doi: 10.19287/j.mtmt.1005-2402.2024.03.016

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The static and modal analyses of the motorized spindle were carried out by NewSpilad software to explore the influence of bearing preload and spindle extended length on the stiffness and natural frequency of the spindle. The results show that adjusting the bearing preload has little effect on the radial stiffness of the spindle, with a change of less than 20%. The axial stiffness has a large influence, and the change amount is more than 50%. The effect on the intrinsic frequency of the spindle is small, and the maximum change is 24%. Increasing the overhang has a small effect on the axial stiffness of the spindle, with a change of 5% or less. The effect on radial stiffness is larger, and the change amount is about 13%. The first-order intrinsic frequency has a tendency to increase. And verified by the spindle static and dynamic accuracy test. Comparison found that the error between the finite element analysis results and the actual test results is within 10%. The results of this study provide a theoretical basis for the spindle static and dynamic characteristics analysis, and further enhance the spindle design and development capabilities.

Mathematical modeling and example application analysis of the positioning pin connection of the rotary fixture in horizontal machining center

LI Shengbin, CHEN Shuai, SONG Wei, WANG Peng, LIU Runjie, XU Xiaoming

2024, (3): 120-125. doi: 10.19287/j.mtmt.1005-2402.2024.03.017

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The typical structure of the rotary fixture for the horizontal machining center turntable is to configure the turntable, tailstock, and clamp on the workbench of the horizontal machining center, thereby forming a cradle type turntable. This method can centralize the machining process, further improve the machining quality and efficiency of the parts. Based on the analysis of the composition type of the cradle type rotary fixture, the positioning pin connection is taken as the research object. By discussing several parallel relationships between the positioning pin connection, the rotary axis of the turntable, and the machine coordinate system, a mathematical model is established, and practical problems encountered in the production process are solved through examples.

Temperature field simulation technology for research in quality control of the reflow process

HOU Wenjing, HE Fei, HU Zixiang

2024, (3): 126-133. doi: 10.19287/j.mtmt.1005-2402.2024.03.018

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This study proposes an innovative simulation method to address quality control issues in the reflow soldering process by analyzing the temperature field. The method considers the influences of thermal convection and thermal radiation, utilizing a single-temperature chamber as the reflow oven and PCB components as the soldered objects. Ansys Icepak software is employed to simulate the reflow soldering process, and an oven temperature test platform is built to monitor the temperature profiles of PCB components, facilitating quality analysis of soldering. The simulation model effectively replicates the reflow temperature distribution among different process parameter groups (A to C), consistently matching the measured temperature profiles. Notably, process parameter group A yields superior solder quality. This innovative approach achieves effective quality control, providing a theoretical foundation for optimizing the reflow soldering process and facilitating adjustments to enhance both soldering performance and productivity. Furthermore, it offers valuable insights for controlling temperature fields in similar processes, making it a valuable reference for various manufacturing applications in the electronics industry.

Research on residual stress in milling GH4169 and parameters optimization

LI Feng, CHEN Zhen, ZHAO Dezhong, LI Wenke

2024, (3): 134-139. doi: 10.19287/j.mtmt.1005-2402.2024.03.019

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GH4169 was widely used in the manufacturing of aerospace hot end components. In order to improve the fatigue life of GH4169 workpieces and improve machining efficiency, an orthogonal experiment was designed between milling parameters and residual stress on the surface of the workpiece. Based on experiments, an empirical formula was established between milling parameters and surface residual stress, and the influence of milling parameters on surface residual stress was analyzed. In addition, genetic algorithm was applied to optimize the milling parameters with the expected values of surface residual stress and material removal rate as the optimization objectives. And the optimization results were experimentally verified. The results indicated that the cutting speed had the greatest impact on the residual stress in the X and Y directions. The influence of feed rate per tooth on the residual stress in the X direction was second,and the influence on the residual stress in the Y direction was the smallest. The influence of cutting depth on the residual stress in the X direction was the smallest, and the influence on the residual stress in the Y direction was the second. A smaller cutting speed and a larger feed rate per tooth were beneficial for obtaining the desired surface residual stress, and changes in cutting depth have a little impact on residual stress.The optimized milling parameter combination was: v_c=26.64 m/min, a_p=0.45 mm, f_z=0.10 mm/z, a_e=0.25 mm, The optimized milling parameters can reduce the residualstress on the surface of GH4169 material and improve cutting efficiency. It can provide a basis for the selection of milling parameters for GH4169 parts.

Research on ultrasonic synergistic cleaning of copper electrode cathode titanium plate silicon carbide suspension

JIANG Peimin, WU Zhangyong, ZHU Qichen, JIANG Jiajun, YANG Wenyong, ZHANG Gang

2024, (3): 140-146. doi: 10.19287/j.mtmt.1005-2402.2024.03.020

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The copper electroplating cathode titanium plate, being an essential constituent of the copper electroplating process, and its surface quality significantly impacts the electrolytic efficiency, quality, and lifespan of the titanium plates themselves. In response to this question, a simple, efficient, and environmentally friendly surface treatment for the titanium plate is employed, utilizing ultrasonic synergistic cleaning technology with a silicon carbide suspension. The optimal cleaning parameters were investigated through an aluminum foil corrosion method, and an analysis of the synergistic effects during the cleaning process and their underlying mechanisms was conducted. Surface cleanliness, micro-morphology and wettability of titanium plates were characterized and evaluated by SEM+EDS and contact angle measurement. The results showed that the best cleaning effect was achieved at a distance of 78 mm from the transducer, a silicon carbide particle mass fraction of 0.05%, a particle size of 70 nm, a neutral pH, and a temperature of 55°C. The synergistic effect of silicon carbide suspension as a cleaning medium can significantly increase the cleaning efficiency and improve the surface quality of titanium plates. Comparison before and after cleaning shows that synergistic cleaning can effectively remove the contaminants on the surface of titanium plate, improve the surface cleanliness and wettability, and restore the surface micro-morphology and metallic luster of titanium plate. The study provides a reference basis for optimizing the cleaning process of titanium plate.

Optimization of selective laser sintering molding processing parameters based on CSO-LSSVM model

JIANG Chenglei, LI Jian, XIAO Yaning, GUO Yanling, WANG Yangwei

2024, (3): 147-155. doi: 10.19287/j.mtmt.1005-2402.2024.03.021

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Molding shrinkage significantly impacts the precision of selective laser sintering (SLS) components, with process parameters playing a critical role in material sintering and shrinkage deformation. Enhancing molding performance quality holds paramount importance. To curtail testing costs in the optimization of process parameters for SLS-molded parts, we introduce the CSO-LSSVM molding accuracy prediction model. The model’s design rationale is multifaceted: first, we comprehensively enhance the convergence accuracy and optimization speed of the snake optimizer (SO) through a trio of improvement strategies—Sine mapping, nonlinear switching factors, and pinhole imaging reverse learning. Subsequently, we seamlessly integrate the termed chaotic multi-strategy enhanced snake optimizer (CSO) with the least square support vector machine (LSSVM) to fine-tune pivotal kernel function parameters, thereby augmenting predictive accuracy and generalization capabilities. To affirm the validity and superiority of the CSO-LSSVM model, we leverage Matlab software for comparative analysis against LSSVM, BP (back propagation) neural network, and extreme learning machine (ELM) models using authentic datasets. Results unequivocally establish the method's heightened predictive accuracy, substantiated by error evaluation metrics: root mean square error of 0.546 2, mean absolute percentage error of 9.487 7, and mean absolute error of 0.401 7, respectively. This model facilitates the provisioning of optimal process parameters for SLS molding, thereby offering effective processing guidance.

Analysis and problem solving of cylinder block balance shaft bore coaxiality deviation

MI Zhaoqiang

2024, (3): 156-160. doi: 10.19287/j.mtmt.1005-2402.2024.03.022

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The root cause of balance shaft bore coaxiality deviation is identified by combining the application of the source of variation analysis, process variation check, and deep dives of CMM measurement result. General variation factor that affects the overall coaxiality performance is eliminated by optimizing the process sequence. Special variation factor of problem concentrated machines is eliminated by multiple machine adjustment methods, thus solving the cylinder block balance shaft bore coaxiality deviation problem.

Fast recognition method of surface defects on micro-steel balls based on improved AlexNet-SVM convolutional neural network

LI Lin, WANG Zhong, WU Xiuli

2024, (3): 161-167. doi: 10.19287/j.mtmt.1005-2402.2024.03.023

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The quality control of surface defects on micro-steel balls is particularly difficult because of high reflectivity and the need for full coverage on the spherical surface. In response to the problems of low efficiency and inadequate accuracy of manual inspection methods, an improved method is proposed for fast identification of surface defects on steel balls with a combination of an improved AlexNet convolutional neural network and an SVM model. The last three convolutional layers are removed and the features extracted by the fully connected layer FC7 are reserved in our model. The original Softmax classifier is replaced by SVM to prevent overfitting and improve the model's generalization ability. In addition, an improved network search algorithm based on K-CV is used to determine optimal parameters for the classifier. Experimental evaluation of the proposed model's recognition results is performed with a confusion matrix. The results show that this method achieves an average accuracy rate of 99.43% with an operating time of 17.2 ms. Compared to the original model and other network models, it has higher accuracy and inference speed, meeting the requirements of industrial field inspection.

Parameter identification of hysteresis model of macro-micro composite actuator based on improved gray wolf algorithm

YU Caofeng, TAO Xuefeng, WEI Yijun, YANG Kun, WANG Ning

2024, (3): 168-172, 192. doi: 10.19287/j.mtmt.1005-2402.2024.03.024

[Abstract] FullText HTML PDF(2056KB)

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The accurate identification of hysteresis model parameters is the key to ensuring the displacement tracking accuracy of macro-micro composite actuators. To address the shortcomings of traditional grey wolf algorithm (GWO), which is prone to local optima and premature convergence, an improved grey wolf algorithm (TGWO) is proposed. Updating the initial position of gray wolf individuals based on Singer chaotic mapping to improve population diversity; Adopting a nonlinear convergence factor strategy to improve local development and global search performance; Introducing dynamic weight updating and adaptive updating strategies in the iterative updating of population positions. Simulation and experiments have shown that this algorithm can effectively and reliably identify the parameters of the hysteresis model of macro-micro composite actuators, The mean relative error is 4.6%, with higher accuracy and convergence.

Finite element model driven rapid localization method for multi-damages on pressure vessels

WANG Changlin, ZHU Gaoliang, ZHONG Yongteng

2024, (3): 173-177. doi: 10.19287/j.mtmt.1005-2402.2024.03.025

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Torispherical structures are one of the main head or bottom cover parts of special equipment such as pressure vessels. Conventional nondestructive testing methods are not quite applicable for online damages inspection at the head or bottom part of large storage tanks in-service. Piezoelectric transducers (PZT) are capable for both exciting and receiving Lamb waves to scan large surface areas and detect damages. This paper constructs a compact uniform circular array using PZTs and presents a virtual array sparse feature based multi-damage localization method for hemispherical head. Firstly, array Lamb wave signal propagating on hemispherical structures is modeling for constructing array sparse features using the array steering vector. Secondly, a finite element analysis model of pressure vessel head was created in ABAQUS to construct virtual array sparse feature library. Finally, their locations can be quickly determined by damages imaging using similarity compared the array steering vector of damage signals with the virtual array sparse feature library. Both the numerical and experimental results verify the virtual array sparse feature modeling based multiple damages localization method can effectively monitor axisymmetric structures with high accuracy.

Solving the JSP problem using a hybrid CHIO algorithm based on quantum computing and Weibull distribution

QI Xiangbo, ZHAO Pinwei, WANG Run

2024, (3): 178-187. doi: 10.19287/j.mtmt.1005-2402.2024.03.026

[Abstract] FullText HTML PDF(1284KB)

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A quantum hybrid coronavirus herd immunity optimizer (QCHIO) algorithm is proposed to address the issues of local optima trapping, slow convergence speed, and poor convergence accuracy in the Coronavirus herd immunity optimizer (CHIO) algorithm. Firstly, the concept of quantum computing is introduced to achieve the goals of global search and fast convergence through quantum correlations, effectively avoiding the problem of the algorithm getting trapped in local optima. Secondly, the algorithm enhances its global exploration capability by utilizing both large and small step sizes of the Weibull distribution operator to increase algorithm diversity and better explore the search space. Additionally, the hill-climbing operator is introduced to search the neighborhood of the current best solution, attempting to find better solutions and thereby increasing the algorithm’s search breadth and improving the quality of solutions. Multi-neighborhood search further enhances the convergence accuracy of the algorithm by searching multiple neighborhoods of the global optimum. To validate its performance, QCHIO is applied to 10 standard test cases and compared with other improved algorithms, demonstrating its superiority through significant testing. Finally, the feasibility and superiority of QCHIO are further demonstrated by applying it to a case of engine production scheduling.

Feature-based component manufacturing cost estimation

LI Tingtai, TAO Jianhua

2024, (3): 188-192. doi: 10.19287/j.mtmt.1005-2402.2024.03.027

[Abstract] FullText HTML PDF(1251KB)

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Because the calculation of parts manufacturing cost relies too much on traditional manual experience, a feature-based method of parts manufacturing cost calculation is proposed to improve the ability of parts manufacturing to respond to dynamic demand changes. By classifying the processing characteristics, the main factors affecting the manufacturing cost were analyzed, the manufacturing cost model of plate parts was defined, and the manufacturing resource database was established. According to the key information of material cost and processing cost, the processing time calculation method based on processing characteristics is deeply analyzed, and the processing cost is determined.

Research on the operating status prediction of workshop equipment based on digital twin and k-nearest neighbor algorithm

HE Zheng, LI Zhongpeng, YANG Xiaohong

2024, (3): 193-199. doi: 10.19287/j.mtmt.1005-2402.2024.03.028

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Abstract:
Due to the inability of traditional workshop equipment operating status prediction to effectively utilize historical data for learning, limited real-time response ability, and difficulty in achieving good results in complex scheduling environments, a workshop equipment operating status prediction model combining digital twin and k-nearest neighbor algorithm is proposed. A digital twin model of workshop equipment entities in the information space is constructed, and then, a mapping relationship between equipment entities and models is also established, in order to obtain real-time feature data, namely equipment operating status feature data. The k-nearest neighbor algorithm is used to calculate the euclidean distance between the real-time feature data and the historical data, that is, to calculate the similarity between the current operating status of the equipment and the known historical status, and finally, based on the historical operating status data of the equipment corresponding to the first k distances, the current operating status of the equipment is predicted. The essence of this model is to collect real-time data from digital twin, obtain characteristic data of designated equipment operating status, and use k-nearest neighbor algorithm to predict the real-time operating status of equipment. Compared to previous studies, the contribution of this study is to improve the accuracy of equipment real-time operating status prediction.If digital twin and k-nearest neighbor algorithm are combined with relevant algorithms with self-learning ability, the predictive performance of the model will be better.

2024, (3): 200-200.

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2024 No. 3

Journal DynamicsMore

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