Table of Content

    10 July 2022, Volume 33 Issue 13
    Dynamics Modeling Method of Complex Rotors for Aero-turboshaft Engines
    WANG Longkai, WANG Ailun, YIN Yijun, JIN Miao, HENG Xing
    2022, 33(13):  1513-1520.  DOI: 10.3969/j.issn.1004-132X.2022.13.001
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    To establish the dynamics model of complex rotor systems in turboshaft engines,the complex structure was modeled by substructure method on the basis of finite element method and piecewise linear fitting. After reducing the degrees of freedom of the systems,motion equations of the rotor systems were derived. The validity of the model was verified by theoretical analysis and experiments,and the vibration characteristics of the gas generator rotors were analyzed. The results show that the established model may significantly reduce the complexity of the overall systems and greatly shorten the calculation time under the premise of ensuring the solution accuracy.
    Design Methodology and Mesh Characteristics of Face-milled Hypoid Gears with Low Crossed Shaft Angle
    LIU Siyuan, SONG Chaosheng, ZHU Caichao
    2022, 33(13):  1521-1528,1536.  DOI: 10.3969/j.issn.1004-132X.2022.13.002
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     A design methodology for hypoid gears in low crossed shaft angle was proposed. The geometric relationships of pitch cones  were derived based on the instantaneous axis of uniparted hyperboloid. Considering the root part smoothness, the mesh behavior controlling methodology of hypoid gears with low crossed shaft angle was proposed. The finite element analysis was performed to investigate the influences of different loads on the mesh behavior. The prototype of hypoid gears proposed may work in low crossed shaft angle stably. 
    Test and Optimization of Nonlinear Vibration Reduction Systems for Loader Cabs
    ZHANG Xin, SUI Zhiwei, LI Zhanlong, QIN Yuan, WANG Yao, DONG Di, ZHAO Junduo
    2022, 33(13):  1529-1536.  DOI: 10.3969/j.issn.1004-132X.2022.13.003
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    Taking the vibration damping system of a loader cab as the research object, the problems of excessive cab vibrations and poor driving comfort were solved by optimization. Firstly, the measured frame vibration signals were used as the input excitation, and the nonlinear vibration damping system model of cab-seat-human body was simplified according to the actual structure of the cabs. The maximum root-mean-square values of vertical vibration acceleration of cab and seat outputs by the model and the actual vehicle test is less than 6%. Then, the root-mean-square values of vertical acceleration of cab and seat were taken as the objectives, and the genetic algorithm was used for multi-objective optimization. Finally, the optimization results were substituted into the model to verify the vibration reduction performance of cab and seat before and after optimization. The real vehicle tests show that the root-mean-square values of vertical acceleration of cabs are reduced as 16% and that of seat are reduced as 53% after improvement.
    Functional Lattice Structures Design Method Based on Strengthening Nodes
    XU Ganjun, DAI Ning
    2022, 33(13):  1537-1544.  DOI: 10.3969/j.issn.1004-132X.2022.13.004
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     Aiming at lattice design of the integration of function and structure, a design method for strengthening lattice structure nodes was proposed based on the analysis results of beam model. Taking the gear as the carrier whose web was filled with lattice structure, a vibration detection platform was built to verify the functional performance of the lattice structures. Experimental results show that compared with the lattice structure with the same mass, the amplitude of the functional lattice structure decreases by 20.90% and the loading capacity increases by 30.00%. 
    Scanning Ablation Characteristic Control for Femtosecond Laser Finishing of Face Gears
    MING Xingzu, XIAO Yongbo, LIU Kefei, ZHOU Xian, ZHANG Haibo, MING Rui
    2022, 33(13):  1544-1550.  DOI: 10.3969/j.issn.1004-132X.2022.13.005
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    Based on the energy accumulation effect of femtosecond laser ablation of flank gears, a three-temperature heat transfer model of coupling between photon-electron-lattice systems was established herein, and a method to determine the scanning distance between femtosecond laser ablation tooth surfaces was proposed. The simulation shows that when the energy density is as 6.47 J/cm2, the equilibrium temperature 3200 K exceeds the melting temperature of materials, and the heat accumulation effect is obvious. The cumulative laser intensity was calculated according to different scanning distances to control the depth and contour of pit ablation. The experimental results show that when the energy density is as 6.47 J/cm2, with the decrease of scanning distance, the laser cumulative intensity increases, and the ablation depth of the tooth surface increases linearly; when the scanning distance is as 25 μm, the machining quality of the gear surfaces is good. 
    Fretting Wear Properties of Nuclear TP316H Steels under Different Medium Environments
    FENG Shuo, CHEN Xudong, TANG Rui, WANG Liwen, ZHANG Fan, CAI Zhenbing
    2022, 33(13):  1551-1559,1603.  DOI: 10.3969/j.issn.1004-132X.2022.13.006
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    Fretting wear tests of TP316H steels under different environments (air/water at room temperature, air/liquid sodium at 450 ℃) were carried out by a self-made fretting wear test rig with the contact configuration of tube-on-rod. After tests, the worn surfaces were examined by a super depth field microscope, 3D optical microscope, SEM(scanning electron microscope) and EDS(energy dispersive spectroscopy) to obtain information on wear morphology, volume and surface chemical compositions. The results show that the highest wear rate of TP316H steels in 450 ℃ liquid sodium and the lowest wear rate is in room temperature water. The wear mechanism of TP316H steels in 4 environments is different. Delamination and oxidative wear are the main wear mechanism in air, and oxidation intensifies with the increase of temperature, while the abrasive wear is dominant in water. The synergistic effect of wear and corrosion is found in liquid sodium at 450 ℃.
    Three-level Orderly Proceeding Optimization Design and Its Applications for Parallel Mechanisms Based on Kinematics,Stiffness and Dynamics
    WANG Yixi, SHEN Huiping, CHEN Pu, WU Guanglei
    2022, 33(13):  1560-1575,1621.  DOI: 10.3969/j.issn.1004-132X.2022.13.007
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    A three-level orderly proceeding optimization methodology was proposed based on kinematics, stiffness and dynamics of PM. The three intelligent algorithms of genetic algorithm(GA), particle swarm algorithm(PSO) and differential evolution(DE) were applied to optimize the dimensional parameters, sectional parameters and mass parameters respectively. Firstly, optimization of the dimensional parameters was aiming at the workspace performance and motion/force transmission performance. Secondly, on the basis of the dimension parameter optimization, the sectional parameters of the components with the objective of the bearing stiffness and overall stiffness of the mechanisms were optimized. Finally, on the basis of the dimensional parameters and sectional parameter optimizations, the mass parameters of the mechanisms were optimized with the objective of dynamics dexterity and energy transmission efficiency. A zero-coupling SCARA PM was used as an example to illustrate the optimization procedure. Firstly, the kinematics model of the PM was established by using vector method, and the dimensional parameters were optimized through the workspace performance and motion/force transmission performance. Secondly, the stiffness model of the PM was obtained by using the virtual spring method, and the flexibility matrix was obtained through the parameter identification of CAD model. Then, the dynamics model of the PM was derived by using the general dynamics equation, and the mass parameters of the components were optimized through the dynamics dexterity and energy transmission efficiency. Thus, the comprehensive performances of kinematics, stiffness and dynamics of the PM reached. Meanwhile, some design criteria of dimensional, sectional and mass parameters were obtained. 
    Neuromuscular Architecture Based Compliance Control of Bionic Parallel Torsos
    ZHU Yaguang, ZHU Jianwei, LI Ruyue, SONG Zhipeng
    2022, 33(13):  1576-1585,1637.  DOI: 10.3969/j.issn.1004-132X.2022.13.008
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     A 6-DOF bionic parallel torso was constructed by mimicking the structure of animal torsos. A neuromuscular control method was proposed to make the bionic parallel torso move flexibly under the impacts of external forces by controlling the stretching of virtual muscles. A neuromuscular control network was established to plan the motion trajectory of the bionic parallel torsos based on rhythm signals generated by nonlinear oscillators. The inverse kinematics was applied to solve the joint rotation angles, and the motor was controlled to drive the bionic parallel torso movement according to the rotation angle information. A virtual muscle model was constructed to drive the torso joints to produce compliant motion under the action of external forces. The simulation model and the physical test results of the parallel torsos show that the method may effectively improve the flexibility of cushioning and fast response of the parallel torsos. 
    Coordinated Guidance Control for Multi-robot Cooperative Transportations of Large-sized Objects
    WU Xing, YU Wenkang, LOU Peihuang, LOU Hangfei, ZHAI Jingjing, HU Zihan
    2022, 33(13):  1586-1595.  DOI: 10.3969/j.issn.1004-132X.2022.13.009
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    The multi-robot cooperative transportation approach had the noteworthy task flexibility and condition adaptability for the manipulation of heavy-duty, large-sized, small-rigidity irregular-shape objects. Firstly, 3 guidance control configurations, mono-camera dual-unit, dual-camera dual-unit, and dual-camera multi-kinematic-pair omni-directional, were investigated for cooperative transportations. The multiple-input and multiple-output motion control models were established. Then, 2 coordinated path tracking control methods were proposed by means of leader-follower strategy which was composed of homogeneous framework based on deviation-conversion prediction control for two robots with fuzzy adjustment of control parameters, and heterogeneous framework based on model prediction control for leader robot and backstepping control for follower robot with reinforcement learning of control parameters. Finally, the multi-robot cooperative transportation prototype systems were developed for the guidance control experiments. The experimental results verify the feasibility and effectiveness of the configurations, models, frameworks, and methods. 
    Multi-condition Monitoring and Fault Diagnosis of Wind Turbines Based on Cointegration Analysis
    WANG Qiancheng, SU Chun, WEN Zejun
    2022, 33(13):  1596-1603.  DOI: 10.3969/j.issn.1004-132X.2022.13.010
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    In order to reduce equipment failure rates and downtime loss, a method for equipments multi-condition monitoring and fault diagnosis was proposed herein based on cointegration analysis. Based on the data collected by the supervisory control and data acquisition system, the random forest feature selection algorithm was used to extract the key feature variables related to equipments failure. By cointegration analysis of the key feature series, the cointegration coefficient was calculated and the cointegration model was established to obtain the optimal residual series, which might reflect the changes of equipments status. Probability plot was applied to analyze the optimal residual series and obtain the interval division of multiple operating situations. The residual warning thresholds corresponding to each operating conditions were determined so as to achieve state monitoring and fault warning. The research results of a certain type of direct-drive wind turbine show that the proposed method may analyze non-stationary time series effectively, monitor the faults of motors and identify the operating situations of the wind turbines by residual threshold, improve the accuracy of fault diagnosis. 
    A Low Carbon Optimization Decision Method for Gear Hobbing Process Parameters Driven by Small Sample Data
    YI Qian, LIU Chun, LI Congbo, YI Shuping, HE Shuang
    2022, 33(13):  1604-1612.  DOI: 10.3969/j.issn.1004-132X.2022.13.011
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    Aiming at the shortages of effective historical data in actual manufaction, a carbon emission prediction and multi-objective optimization model driven by small sample data was proposed. The Box-Behnken experimental design was used to collect processing data, and then the back propagation neural network was used to establish a prediction model for carbon emissions and processing efficiency, which ensured the prediction accuracy with less historical sample data. Aiming to optimize the total carbon consumption and makespan, the improved gray wolf optimization algorithm and entropy-TOPSIS comprehensive evaluation were used for determining the optimal processing parameters. Finally, the effectiveness of the proposed method was verified by machining experiments. 
    Bearing Fault Diagnosis Based on SA-ACGAN Data Generation Model
    YANG Guangyou, LIU Lang, XI Chenbo
    2022, 33(13):  1613-1621.  DOI: 10.3969/j.issn.1004-132X.2022.13.012
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    Unbalancing training dataset caused by the difficulty in obtaining fault samples seriously affectsed the robust and accuracy of fault diagnosis model. A data generation model was proposed based on self-adaptive auxiliary classifier GAN, which adaptively adjusted the generator loss by measuring the relative performance between discriminator and generator, accelerated the converge speed of training processes, and improved the quality of generated data. The raw data, data generated by auxiliary classifier GAN method, and data generated by proposed method were used as the input data of the BP neural network. The results show that the model trained by data of the proposed method was superior. Comparison results of the proposed method with 1D-CNN,e2e-LSTM,CFVS-SVM, and FFT-CNN fault diagnosis methods manifest that the proposed method is better in fault diagnosis accuracy and data processing time
    Optimization of First Deep Drawing Process Parameters for Power Battery Shells Based on Entropy Weight Comprehensive Evaluation Method
    REN Zhenbao, CAO Chunping
    2022, 33(13):  1622-1628.  DOI: 10.3969/j.issn.1004-132X.2022.13.013
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    Aiming at the problems of wrinkling, cracking, uneven thickness, and large die contact force in the first deep drawing processes of a power battery case, based on entropy weight a comprehensive evaluation method was proposed to optimize the processing parameters of the first deep drawing processes, so as to improve the quality of the first deep drawing processes. Orthogonal experimental simulation was carried out with the influencing factors such as blank-holder force, die radius, punch radius, die clearance, and friction factor, and the evaluation index such as maximum reduction ratio, maximum thickness ratio, maximum limit punch contact force, and maximum differential thickness. Based on the applications of entropy value method and the comprehensive evaluation method, the optimum technological parameters combination was obtained, and the forming quality of the first passes of the power battery cases is improved. 
    Low-velocity-impact Resistance Property of Sandwich Plates with Aluminum Folded Core
    YANG Jingjing, LI Cheng, TIE Ying
    2022, 33(13):  1629-1637.  DOI: 10.3969/j.issn.1004-132X.2022.13.014
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    Two major geometric approaches of anti-impact property optimization in sandwich plates with aluminum folded core were studied by FEM. Impact resistance of the sandwich panels was enhanced by increasing of panel thickness and core wall thickness, while increasing core wall thickness gave the structure better energy absorption characteristics and efficiency. In real case, sandwich products were subjected to random impact load in service life, damages in sandwich plates caused by different impact angles were compared. The results show that with the increase of impact angle, damages of sandwich plates decrease, the damages of folded core gradually decrease than that of upper panel, and energy absorptions of the sandwich panel decrease.