• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
ZHU Honglin, SONG Shuai, WU Yudong, YANG Mingliang, SHUI Yongbo, DING Weiping. Evaluation of Vehicle Road Impact Sound Quality Based on Time-Frequency Perception Weighting[J]. Journal of Southwest Jiaotong University, 2023, 58(2): 296-303. doi: 10.3969/j.issn.0258-2724.20211060
Citation: XU Chengcheng, XU Fangchao, SUN Feng, ZHANG Xiaoyou, JIN Junjie, LUAN Boran. Micro-positioning Control of Magnetic Actuator for Electrical Discharge Machining[J]. Journal of Southwest Jiaotong University, 2022, 57(3): 610-617. doi: 10.3969/j.issn.0258-2724.20210987

Micro-positioning Control of Magnetic Actuator for Electrical Discharge Machining

doi: 10.3969/j.issn.0258-2724.20210987
  • Received Date: 30 Nov 2021
  • Rev Recd Date: 22 Mar 2022
  • Publish Date: 31 Mar 2022
  • For timely controlling the gap between poles in electrical discharge machining (EDM), a single-degree-of-freedom magnetic actuator is designed with merits of high precision, fast response, wide frequency band and long stroke. As the local actuator in EDM, it is optimized by a fuzzy PID control method that modify the control parameters online and in real time. Firstly, the dynamic model of the magnetic actuator device is analyzed, and the transformation relationship is built between the coil current and the mover displacement in the magnetic actuator. Secondly, a conventional PID controller is designed according to the characteristics of the magnetic actuator device, and fuzzy control is introduced to optimize the performance of micro-positioning control. Finally, the controller performance is verified by the micro-positioning simulation and experiment on the magnetic actuator. Simulation and experimental results show that the magnetic actuator has a micron-level positioning resolution, a wide frequency band greater than 50 Hz, and a positioning stroke of 2 mm, which fully meets the fine-tuning requirements of EDM.

     

  • [1]
    LI H, DENG Z, HUANG H, et al. Experiments and simulations of the secondary suspension system to improve the dynamic characteristics of HTS maglev[J]. IEEE Transactions on Applied Superconductivity, 2021, 31(6): 1-8.
    [2]
    蒋启龙,梁达,阎枫. 数字单周期电流控制在电磁悬浮系统中的应用[J]. 西南交通大学学报,2019,54(1): 1-8, 22.

    JIANG Qilong, LIANG Da, YAN Fang. Application of Digital One-Cycle Control for Current in Electromagnetic Suspension System[J]. Journal of Southwest Jiaotong University, 2019, 54(1): 1-8, 22.
    [3]
    张伟煜,朱熀秋,袁野. 磁悬浮轴承应用发展及关键技术综述[J]. 电工技术学报,2015,30(12): 12-20. doi: 10.3969/j.issn.1000-6753.2015.12.002

    ZHANG Weiyu, ZHU Huangqiu, YUAN Ye. Study on key technologies and Applications of magnetic bearings[J]. Transactions of China Electrotechnical Society, 2015, 30(12): 12-20. doi: 10.3969/j.issn.1000-6753.2015.12.002
    [4]
    姚京京,郑德智,马康,等. 多轴悬浮式低频振动传感器的理论研究[J]. 北京航空航天大学学报,2018,44(7): 1481-1488.

    YAO Jingjing, ZHENG Dezhi, MA Kang, et al. Theoretical research on muti-axis maglev low-frequency vibration sensor[J]. Journal of Beijing University of Aeronautics and Astronautic, 2018, 44(7): 1481-1488.
    [5]
    郜浩楠,徐俊,蒲晓晖,等. 面向新能源汽车的悬架振动能量回收在线控制方法[J]. 西安交通大学学报,2020,54(4): 19-26.

    GAO Haonan, XU Jun, PU Xiaohui, et al. An online control method for energy recovery of suspension vibration of new energy vehicles[J]. Journal of Xi’an Jiaotong University, 2020, 54(4): 19-26.
    [6]
    ZHU H Y, TEO D, PANG C K. Magnetically levitated parallel actuated dual-stage (Maglev-PAD) system for six-axis precision positioning[J]. Transactions on Mechatronics, 2019, 24(4): 1829-1838. doi: 10.1109/TMECH.2019.2928978
    [7]
    李红伟,范友鹏,张云鹏,等. 轴流式人工心脏泵混合磁悬浮系统的耦合特性[J]. 电机与控制学报,2014,18(5): 105-111. doi: 10.3969/j.issn.1007-449X.2014.05.017

    LI Hongwei, FAN Youpeng, ZHANG Yunpeng. Coupling in hybrid magnetic levitation system of axial-flow blood pump[J]. Electric Machines and Control, 2014, 18(5): 105-111. doi: 10.3969/j.issn.1007-449X.2014.05.017
    [8]
    佟玲,吴利平,金嘉琦,等. 激光焦点控制磁力驱动的控制特性实验对比分析[J]. 国防科技大学学报,2018,40(3): 120-126. doi: 10.11887/j.cn.201803019

    TONG Ling, WU Lingping, JIN Jiaqi, et al. Experimental comparative analysis of control characteristics of laser focus control magnetic force drive[J]. Journal of National University of Defense Technology, 2018, 40(3): 120-126. doi: 10.11887/j.cn.201803019
    [9]
    FENG Y, GUO Y F, LING Z B, et al. Micro-holes EDM of superalloy Inconel 718 based on a magnetic suspension spindle system[J]. Journal of Advanced Manufacturing Technology, 2019, 101(5/6/7/8): 2015-2026. doi: 10.1007/s00170-018-3075-6
    [10]
    FENG Y, GUO Y F, LING Z B, et al. Investigation on machining performance of micro-holes EDM in ZrB2-SiC ceramics using a magnetic suspension spindle system[J]. The International Journal of Advanced Manufacturing Technology, 2019, 101(5): 2083-2095.
    [11]
    ZHANG X Y, TADAHIKO S, AKIRA S. High-speed electrical discharge machining by using a 5-DOF controlled maglev local actuator[J]. Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2008, 2(4): 493-503. doi: 10.1299/jamdsm.2.493
    [12]
    REPINALDO J P, KOROISHI E H, LARA-MOLINA F A, et al. Neuro-fuzzy control applied on a 2DOF structure using electromagnetic actuators[J]. IEEE Latin America Transactions, 2021, 19(1): 75-82. doi: 10.1109/TLA.2021.9423849
    [13]
    LI X H, WAN S K, YUAN J P, et al. Active suppression of milling chatter with LMI-based robust controller and electromagnetic actuator[J]. Journal of Materials Processing Technology, 2021, 297: 117238. doi: 10.1016/j.jmatprotec.2021.117238
    [14]
    ZHENG T, XU X Z, LU X, et al. Learning adaptive sliding mode control for repetitive motion tasks in maglev rotary table[J]. Transactions on Industrial Electronics, 2021, 69(2): 1836-1846.
    [15]
    朱熀秋, 顾志伟. 基于模糊神经网络逆系统的五自由度无轴承永磁同步电机自抗扰控制[J]. 电机与控制学报,2021,25(2): 72-81.

    ZHU Huangqiu, GU Zhiwei. Active disturbance rejection control for 5-degree-of-freedom bearingless permanent magnet synchronous motor based on inverse system using the fuzzy neural network[J]. Electric Machines and Control, 2021, 25(2): 72-81.
    [16]
    CHEN J W. Modeling and decoupling control of a linear permanent magnet actuator considering fringing effect for precision engineering[J]. IEEE Transactions on Magnetics, 2021, 57(3): 1965-2012.
    [17]
    林超力,刘鸿飞,孙惠军,等. 模糊自适应PID算法在核磁共振谱仪样品旋转控制系统中的应用[J]. 分析化学,2011,39(4): 506-510.

    LIN Chaoli, LIU Hongfei, SUN Huijun, et al. Implementation of fuzzy self-tuning proportional integral derivative controller on sample-tube spin control system in nuclear magnetic resonance spectrometer[J]. Chinese Journal of Analytical Chemistry, 2011, 39(4): 506-510.
    [18]
    ZHANG X Y, UEYAMA Y, SHINSHI T, ec al. High-speed and high-accuracy EDM of micro holes by using a 5-DOF controlled maglev local actuator[J]. Materials Science Forum, 2009, 2(4): 255-260.
  • Relative Articles

    [1]BAO Yanyan, YANG Guangze, CHEN Wei, FENG Tingna. Voiceprint Recognition of 750 kV Transformer and Pin-Plate Discharge Aliasing Signals Based on Sparse Representation Theory and Convolutional Neural Network[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20230177
    [2]LI Linchao, ZHONG Liangjian, SU Qing, REN Lu, DU Bowen. Fine Urban Land Use Identification Based on Fusion of Multi-source Data[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20230296
    [3]ZHANG Hong, JIANG Xiaogang, ZHU Zhiwei, XIA Runchuan, ZHOU Jianting. Review on Intelligent Image Recognition of Apparent Diseases of Stay Cable[J]. Journal of Southwest Jiaotong University, 2025, 60(1): 10-26. doi: 10.3969/j.issn.0258-2724.20220647
    [4]LIU Hongen, HU Minsheng, HU Hailin. Reinforcement Learning Braking Control of Maglev Trains Based on Self-Learning of Hybrid Braking Features[J]. Journal of Southwest Jiaotong University, 2024, 59(4): 839-847. doi: 10.3969/j.issn.0258-2724.20230517
    [5]YANG Yanchun, YAN Yan, WANG Ke. Infrared and Visible Image Fusion Based on Attention Mechanism and Illumination-Aware Network[J]. Journal of Southwest Jiaotong University, 2024, 59(5): 1204-1214. doi: 10.3969/j.issn.0258-2724.20230529
    [6]YUE Chuan, WANG Lide, YAN Haipeng. Attack-Sample Generation Method for Train Communication Network Under Few-Shot Condition[J]. Journal of Southwest Jiaotong University, 2023, 58(6): 1277-1285. doi: 10.3969/j.issn.0258-2724.20210557
    [7]WANG Yaodong, ZHU Liqiang, YU Zujun, SHI Hongmei, SHE Changmei. Intelligent Tunnel Crack Recognition Based on Automatic Sample Labeling[J]. Journal of Southwest Jiaotong University, 2023, 58(5): 1001-1008, 1036. doi: 10.3969/j.issn.0258-2724.20210092
    [8]XIA Ying, LIU Min. Traffic Flow Prediction Based on Spatial-Temporal Attention Convolutional Neural Network[J]. Journal of Southwest Jiaotong University, 2023, 58(2): 340-347. doi: 10.3969/j.issn.0258-2724.20210526
    [9]WANG Yin, WANG Lide, QIU Ji. Real-Time Enhancement Algorithm Based on DenseNet Structure for Railroad Low-Light Environment[J]. Journal of Southwest Jiaotong University, 2022, 57(6): 1349-1357. doi: 10.3969/j.issn.0258-2724.20210199
    [10]PENG Bo, TANG Ju, ZHANG Yuanyuan, CAI Xiaoyu, MENG Fanhe. Automatic Traffic State Recognition from Road Videos Based on 3D Convolution Neural Network[J]. Journal of Southwest Jiaotong University, 2021, 56(1): 153-159. doi: 10.3969/j.issn.0258-2724.20191169
    [11]LI Zechen, LI Hengchao, HU Wenshuai, YANG Jinyu, HUA Zexi. Masked Face Detection Model Based on Multi-scale Attention-Driven Faster R-CNN[J]. Journal of Southwest Jiaotong University, 2021, 56(5): 1002-1010. doi: 10.3969/j.issn.0258-2724.20210017
    [12]YUAN Fei, ZHAO Xuyan, WANG Yige, ZHAO Zhisheng. Smoke Recognition Algorithm Based on Lightweight Convolutional Neural Network[J]. Journal of Southwest Jiaotong University, 2020, 55(5): 1111-1116, 1132. doi: 10.3969/j.issn.0258-2724.20190777
    [13]TIAN Sheng, ZHANG Jianfeng, ZHANG Yutian, XU Kai. Lane Detection Algorithm Based on Dilated Convolution Pyramid Network[J]. Journal of Southwest Jiaotong University, 2020, 55(2): 386-392, 416. doi: 10.3969/j.issn.0258-2724.20181026
    [14]YANG Gang, LI Hengchao, TAN Bei, SHI Chaoqun, ZHANG Xueqin, GUO Yujun, WU Guangning. Application of Hierarchical Extreme Learning Machine in Prediction of Insulator Pollution Degree Using Hyperspectral Images[J]. Journal of Southwest Jiaotong University, 2020, 55(3): 579-587. doi: 10.3969/j.issn.0258-2724.20190093
    [15]XIANG Yu, CONG Deming, ZHANG Yang, YUAN Fei. Two-Stream Neural Network Fusion Model for Highway Fog Detection[J]. Journal of Southwest Jiaotong University, 2019, 54(1): 173-179. doi: 10.3969/j.issn.0258-2724.20180205
    [16]HOU Jin, LÜ Zhiliang, XU Mao, WU Peijun, LIU Yuling, ZHANG Xiaoyu, CHENG Zeng. Combined Neural Networks Based on Deep Learning for Signal Detection in Aeronautical Communications[J]. Journal of Southwest Jiaotong University, 2019, 54(4): 863-869, 878. doi: 10.3969/j.issn.0258-2724.20180164
    [17]HUANG Haibo, LI Renxian, YANG Qi, DING Weiping, YANG Mingliang. Identifying Abnormal Noise of Vehicle Suspension Shock Absorber Based on Deep Belief Networks[J]. Journal of Southwest Jiaotong University, 2015, 28(5): 776-782. doi: 10.3969/j.issn.0258-2724.2015.05.002
    [18]ZHANG Huailiang, LIU Sen, ZOU Baiwen. Assessment Method of Gear Wear Condition Based on Data Mining[J]. Journal of Southwest Jiaotong University, 2015, 28(4): 710-716. doi: 10.3969/j.issn.0258-2724.2015.04.021
    [19]YE Li-sheng, HE Feng-dao. The Learning of BP Neural Network Based on Evolutionary Programming[J]. Journal of Southwest Jiaotong University, 2001, 14(5): 545-548.
    [20]HE Zheng-You, Jian-Qing-Quan. An Improved Wavelet Neural Network Structure and Its Learning Algorithm[J]. Journal of Southwest Jiaotong University, 1999, 12(5): 436-440.
  • Cited by

    Periodical cited type(2)

    1. 雷建新,高志龙,张文波,江志农,辛博. 滚珠丝杠副动力学行为仿真及滚珠磨损故障特征信号研究. 机床与液压. 2024(10): 161-167 .
    2. 陶祝同,王国志,李荣铎. 接触网设备检查机器人结构设计. 机械传动. 2023(09): 44-51 .

    Other cited types(4)

  • Created with Highcharts 5.0.7Amount of accessChart context menuAbstract Views, HTML Views, PDF Downloads StatisticsAbstract ViewsHTML ViewsPDF Downloads2024-052024-062024-072024-082024-092024-102024-112024-122025-012025-022025-032025-040510152025
    Created with Highcharts 5.0.7Chart context menuAccess Class DistributionFULLTEXT: 39.4 %FULLTEXT: 39.4 %META: 57.1 %META: 57.1 %PDF: 3.5 %PDF: 3.5 %FULLTEXTMETAPDF
    Created with Highcharts 5.0.7Chart context menuAccess Area Distribution其他: 8.1 %其他: 8.1 %China: 0.2 %China: 0.2 %[]: 0.5 %[]: 0.5 %上海: 1.4 %上海: 1.4 %临汾: 0.3 %临汾: 0.3 %佛山: 0.2 %佛山: 0.2 %保定: 0.2 %保定: 0.2 %六盘水: 0.2 %六盘水: 0.2 %凤凰城: 0.2 %凤凰城: 0.2 %北京: 6.5 %北京: 6.5 %十堰: 0.2 %十堰: 0.2 %南京: 1.6 %南京: 1.6 %南昌: 0.3 %南昌: 0.3 %台州: 0.3 %台州: 0.3 %名古屋: 0.5 %名古屋: 0.5 %哥伦布: 0.3 %哥伦布: 0.3 %喀什: 0.2 %喀什: 0.2 %大连: 0.2 %大连: 0.2 %天津: 0.6 %天津: 0.6 %宁波: 0.2 %宁波: 0.2 %宜宾: 0.2 %宜宾: 0.2 %宣城: 0.2 %宣城: 0.2 %常州: 0.3 %常州: 0.3 %张家口: 2.5 %张家口: 2.5 %德阳: 0.2 %德阳: 0.2 %成都: 2.4 %成都: 2.4 %扬州: 0.5 %扬州: 0.5 %揭阳: 0.2 %揭阳: 0.2 %无锡: 0.8 %无锡: 0.8 %杭州: 0.2 %杭州: 0.2 %武汉: 0.9 %武汉: 0.9 %池州: 1.4 %池州: 1.4 %沈阳: 0.3 %沈阳: 0.3 %泰安: 0.2 %泰安: 0.2 %洛阳: 0.9 %洛阳: 0.9 %济南: 0.6 %济南: 0.6 %温州: 0.2 %温州: 0.2 %湖州: 0.2 %湖州: 0.2 %漯河: 2.1 %漯河: 2.1 %潍坊: 0.2 %潍坊: 0.2 %烟台: 0.2 %烟台: 0.2 %石家庄: 1.3 %石家庄: 1.3 %福州: 0.2 %福州: 0.2 %自贡: 0.2 %自贡: 0.2 %芒廷维尤: 16.3 %芒廷维尤: 16.3 %芝加哥: 0.9 %芝加哥: 0.9 %衢州: 0.2 %衢州: 0.2 %西宁: 35.8 %西宁: 35.8 %西安: 1.3 %西安: 1.3 %诺沃克: 1.3 %诺沃克: 1.3 %贵阳: 0.3 %贵阳: 0.3 %赣州: 0.2 %赣州: 0.2 %赤峰: 0.2 %赤峰: 0.2 %运城: 0.9 %运城: 0.9 %通辽: 0.3 %通辽: 0.3 %邯郸: 0.5 %邯郸: 0.5 %邵阳: 0.2 %邵阳: 0.2 %郑州: 0.6 %郑州: 0.6 %银川: 0.2 %银川: 0.2 %长春: 0.2 %长春: 0.2 %长沙: 2.4 %长沙: 2.4 %雷德蒙德: 0.2 %雷德蒙德: 0.2 %青岛: 0.3 %青岛: 0.3 %马鞍山: 0.2 %马鞍山: 0.2 %其他China[]上海临汾佛山保定六盘水凤凰城北京十堰南京南昌台州名古屋哥伦布喀什大连天津宁波宜宾宣城常州张家口德阳成都扬州揭阳无锡杭州武汉池州沈阳泰安洛阳济南温州湖州漯河潍坊烟台石家庄福州自贡芒廷维尤芝加哥衢州西宁西安诺沃克贵阳赣州赤峰运城通辽邯郸邵阳郑州银川长春长沙雷德蒙德青岛马鞍山

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(11)  / Tables(4)

    Article views(270) PDF downloads(15) Cited by(6)
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return