CN 41-1243/TG ISSN 1006-852X
Volume 43 Issue 2
Apr.  2023
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Article Contents
ZHAO Biao, LEI Xiaofei, CHEN Tao, DING Wenfeng, FU Yucan, XU Jiuhua, LI Hai. Simulation and intelligent control during grinding process for difficult-to-machine materials in aerospace[J]. Diamond & Abrasives Engineering, 2023, 43(2): 127-143. doi: 10.13394/j.cnki.jgszz.2023.1002
Citation: ZHAO Biao, LEI Xiaofei, CHEN Tao, DING Wenfeng, FU Yucan, XU Jiuhua, LI Hai. Simulation and intelligent control during grinding process for difficult-to-machine materials in aerospace[J]. Diamond & Abrasives Engineering, 2023, 43(2): 127-143. doi: 10.13394/j.cnki.jgszz.2023.1002

Simulation and intelligent control during grinding process for difficult-to-machine materials in aerospace

doi: 10.13394/j.cnki.jgszz.2023.1002
Funds:  Science Center for Gas Turbine Project (P2022-A-IV-002-001), National Natural Science Foundation of China (52205475), Natural Science Foundation of Jiangsu Province ( BK20210295), Superior Postdoctoral Project of Jiangsu Province (2022ZB215), National Key Laboratory of Science and Technology on Helicopter Transmission (HTL-A-22G12)
More Information
  • Author Bio:

    ZHAO Biao (1991—), Male, Ph.D., Lecturer, Research focus: mechanism and process optimization in grinding of difficult-to-cut materials

  • Corresponding author: Email: Corresponding author: DING Wen-feng (1978—), Male, Ph.D., Professor, Research focus: high-efficiency precision machining technology and applications on difficult-to-cut materials.
  • Received Date: 2023-02-24
  • Accepted Date: 2023-03-08
  • Rev Recd Date: 2023-03-05
  • The difficult-to-machine materials (e.g. titanium alloys, superalloys, intermetallics and high-strength steels, etc) have attracted increasing attentions in manufacturing the key components in aerospace fields in recent years, resulting from their superior mechanical properties. Grinding, as the final machining method, has been employed to fabricate those materials and the associated key components, playing an important influence in the manufacturing quality and efficiency. However, there are problems such as large grinding force and temperature, severe wear of wheels, and poor grinding quality, owing to the difficult machining property of those materials and the complexity of grinding processes. This paper summarized the research progresses and existed problems in view of the grinding force, the grinding temperature, the wheel wear and the ground surface quality. The research object was the difficult-to-machine materials in aerospace fields and the main discussion topics focused on the simulation during grinding processes and intelligent control techniques. Finally, the future development trends of grinding process simulation and intelligent control technology were prospected regarding the main problems existing in current researches.


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  • [1]
    李本凯, 丁文锋, 马艳艳, 等. 新型刚玉砂轮磨削GH4169镍基高温合金的性能评价研究 [J]. 航空制造技术,2021,64(4):14-19. doi: 10.16080/j.issn1671-833x.2021.04.014

    LI Benkai, DING Wenfeng, MA Yanyan, et al. Performance evaluation on grinding of nickel-based superalloy GH4169 using new corundum abrasive wheel [J]. Aeronautical Manufacturing Technology,2021,64(4):14-19. doi: 10.16080/j.issn1671-833x.2021.04.014
    KUANG W J, MIAO Q, DING W F, et al. Fretting wear behaviour of machined layer of nickel-based superalloy produced by creep-feed profile grinding [J]. Chinese Journal of Aeronautics,2021,35:401-411. doi: 10.1016/j.cja.2021.10.007
    韩璐, 康仁科, 张园, 等. GH4169超声辅助磨削表面完整性研究 [J]. 金刚石与磨料磨具工程,2021,41(5):46-51. doi: 10.13394/j.cnki.jgszz.2021.5.0008

    HAN Lu, KANG Renke, ZHANG Yuan, et al. Research on surface integrity of GH4169 machined by ultrasonic assisted grinding [J]. Diamond and Abrasives Engineering,2021,41(5):46-51. doi: 10.13394/j.cnki.jgszz.2021.5.0008
    LI H N, YU T B, ZHU L D, et al. Modeling and simulation of grinding wheel by discrete element method and experimental validation [J]. The International Journal of Advanced Manufacturing Technology,2015,81:1921-1938. doi: 10.1007/s00170-015-7205-0
    LI H N, YU T B, WANG Z X, et al. Detailed modeling of cutting forces in grinding process considering variable stages of grain-workpiece micro interactions [J]. International Journal of Mechanical Sciences,2017,126:319-339. doi: 10.1016/j.ijmecsci.2016.11.016
    LI H N, AXINTE D. On a stochastically grain-discretized model for 2D/3D temperature mapping prediction in grinding [J]. International journal of Machine Tools and Manufacture,2017,116:60-76. doi: 10.1016/j.ijmachtools.2017.01.004
    赵庆军, 尹胜, 向瑶, 等. 基于ABAQUS切削仿真加工技术应用 [J]. 工具技术,2022,56(2):76-80. doi: 10.3969/j.issn.1000-7008.2022.02.017

    ZHAO Qingjun, YIN Sheng, XIANG Yao, et al. Application of cutting simulation technology based on ABAQUS [J]. Tool Engineering,2022,56(2):76-80. doi: 10.3969/j.issn.1000-7008.2022.02.017
    WEN J, TANG J Y, ZHOU W H. Study on formation mechanism and regularity of residual stress in ultrasonic vibration grinding of high strength alloy steel [J]. Journal of Manufacturing Processes,2021,66:608-622. doi: 10.1016/j.jmapro.2021.04.040
    闫艳燕, 闫浩哲, 刘俊利, 等. TC4钛合金纵扭超声磨削力热耦合模型及其试验研究 [J]. 中国机械工程,2022,10:1-13. doi: 10.3969/j.issn.1004-132X.2017.01.001

    Yan Yanyan, Yan Hanzhe, Liu Junli. et al. The thermo-mechanical coupling model and experimental research of longitudinal and torsional ultrasonic grinding of TC4 titanium alloy [J]. China Mechanical Engineering,2022,10:1-13. doi: 10.3969/j.issn.1004-132X.2017.01.001
    LEI X F, XIANG D H, PENG P C, et al. Establishment of dynamic grinding force model for ultrasonic-assisted single abrasive high-speed grinding [J]. Journal of Materials Processing Technology,2022,300:117420. doi: 10.1016/j.jmatprotec.2021.117420
    张银霞, 韩程宇, 杨鑫, 等. GCr15钢平面磨削力仿真分析与实验研究 [J]. 表面技术,2019,48(10):342-348. doi: 10.16490/j.cnki.issn.1001-3660.2019.10.042

    ZHANG Yinxia, HAN Chengyu, YANG Xin, et al. Simulation analysis and experimental research on surface grinding force of GCr15 steel [J]. Surface Technology,2019,48(10):342-348. doi: 10.16490/j.cnki.issn.1001-3660.2019.10.042
    MOSLEH A O, MIKHAYLOVSKAYA A V, KOTOV A D, et al. Experimental, modelling and simulation of an approach for optimizing the superplastic forming of Ti-6% Al-4% V titanium alloy [J]. Journal of Manufacturing Processes,2019,45:262-272. doi: 10.1016/j.jmapro.2019.06.033
    YASMEEN T, SHAO Z T, ZHAO L, et al. Constitutive modeling for the simulation of the superplastic forming of TA15 titanium alloy [J]. International Journal of Mechanical Sciences,2019,164:105178. doi: 10.1016/j.ijmecsci.2019.105178
    夏江, 丁文锋, 仇博, 等. 镍基高温合金高速超高速磨削成屑过程的三维仿真研究 [J]. 金刚石与磨料磨具工程,2020,40(6):58-69. doi: 10.13394/j.cnki.jgszz.2020.6.0011

    XIA Jiang, DING Wenfeng, QIU Bo, et al. 3D simulation study on the chip formation process in high speed and ultra-high speed grinding of nickel-based superalloy [J]. Diamond and Abrasives Engineering,2020,40(6):58-69. doi: 10.13394/j.cnki.jgszz.2020.6.0011
    田欣利, 王龙, 刘谦, 等. 20CrMnTi钢齿面磨削力模型构建与分析 [J]. 机械工程学报,2018,54(3):227-232. doi: 10.3901/JME.2018.03.227

    TIAN Xinli, WANG Long, LIU Qian, et al. Construction and analysis of grinding force model of 20CrMnTi steel tooth surface [J]. Journal of Mechanical Engineering,2018,54(3):227-232. doi: 10.3901/JME.2018.03.227
    段继豪, 牛强, 杨元, 等. TC4钛合金磨削机理和仿真研究 [J]. 计算机仿真,2022,39(1):218-232. doi: 10.3969/j.issn.1006-9348.2022.01.047

    DUAN Jihao, NIU Qiang, YANG Yuan, et al. Study on grinding mechanism and simulation of TC4 titanium alloy [J]. Computer Simulation,2022,39(1):218-232. doi: 10.3969/j.issn.1006-9348.2022.01.047
    LI B K, DAI C W, DING W F, et al. Prediction on grinding force during grinding powder metallurgy nickel-based superalloy FGH96 with electroplated CBN abrasive wheel [J]. Chinese Journal of Aeronautics,2021,34(8):65-74. doi: 10.1016/j.cja.2020.05.002
    MA X F, CAI Z Q, YAO B, et al. Dynamic grinding force model for face gear based on the wheel-gear contact geometry [J]. Journal of Materials Processing Technology,2022,306:117633. doi: 10.1016/j.jmatprotec.2022.117633
    马志飞, 梁国星, 张昊, 等. 单颗磨粒高速磨削Ti6Al4V仿真与试验验证 [J]. 工具技术,2019,53(4):49-53. doi: 10.3969/j.issn.1000-7008.2019.04.012

    MA Zhifei, LIANG Guoxing, ZHANG Hao, et al. Simulation and experimental investigation of high-speed grinding Ti6Al4V with single grain [J]. Tool Engineering,2019,53(4):49-53. doi: 10.3969/j.issn.1000-7008.2019.04.012
    GRIMMERT A, WIEDERKEHR P. Macroscopic process simulation of surface and profile grinding processes estimating forces for the production of turbine blades [J]. Procedia CIRP,2021,102:126-131. doi: 10.1016/j.procir.2021.09.022
    NOSENKO V A, DANILENKO M V. Mathematical simulation of cutting force during grinding using theory of Markov processes [J]. Materials Today:Proceedings,2021,38:1602-1606. doi: 10.1016/j.matpr.2020.08.163
    GHANDEHARIUN A, HUSSEIN H M, KISHAWY H A. Machining metal matrix composites: novel analytical force model [J]. International Journal of Advanced Manufacturing Technology,2016,83:233-241. doi: 10.1007/s00170-015-7554-8
    谢黎明, 邹崇磊, 沈浩, 等. 冷作磨具钢Cr12MoV磨削温度场解析模型的建立 [J]. 机械与电子,2010,2:126-131. doi: 10.3969/j.issn.1001-2257.2010.02.023

    XIE Liming, ZOU Chonglei, SHEN Hao, et al. Establishment of analytical model in grinding temperature field of cold steel Cr12MoV [J]. Machinery and electronics,2010,2:126-131. doi: 10.3969/j.issn.1001-2257.2010.02.023
    JIANG J L, GE P Q, SUN S F, et al. From the microscopic interaction mechanism to the grinding temperature field: an integrated modelling on the grinding process [J]. International Journal of Machine Tools and Manufacture,2016,110:27-42. doi: 10.1016/j.ijmachtools.2016.08.004
    JAMSHIDI H, BUDAK E. Grinding temperature modeling based on a time dependent heat source [J]. Procedia CIRP,2018,77:299-302. doi: 10.1016/j.procir.2018.09.020
    YANG S Y, CHEN W F, NONG S, et al. Temperature field modelling in the form grinding of involute gear based on high-order function moving heat source [J]. Journal of Manufacturing Processes,2022,81:1028-1039. doi: 10.1016/j.jmapro.2022.07.014
    CHEN T, MIAO Q, XIONG M Y, et al. On the residual stresses of turbine blade root of γ-TiAl intermetallic alloys induced by non-steady-state creep feed profile grinding [J]. Journal of Manufacturing Processes,2022,82:800-817. doi: 10.1016/j.jmapro.2022.08.051
    王龙, 汪刘应, 唐修检, 等. 成形法磨削齿轮的磨削温度模型构建与分析 [J]. 机械工程学报,2022,58(3):295-304. doi: 10.3901/JME.2022.03.295

    WANG Long, WANG Liuying, TANG Xiujian, et al. Construction and analysis of grinding temperature model for gear processed by form grinding technology [J]. Journal of Mechanical Engineering,2022,58(3):295-304. doi: 10.3901/JME.2022.03.295
    HANDA D, KUMAR S, SURENDRAN S B, et al. Simulation of intermittent grinding for Ti-6Al-4V with segmented wheel [J]. Materials Today: Proceedings,2021,44:2537-2542. doi: 10.1016/j.matpr.2020.12.626
    NASKAR A, CHOUDHARY A, PAUL S. Wear mechanism in high-speed superabrasive grinding of titanium alloy and its effect on surface integrity [J]. Wear,2020,462:203475.
    蓝善超, 王宏芳, 李文斌. 磨料粒度对电镀CBN砂轮磨损影响的有限元仿真分析 [J]. 工具技术,2012,46(1):21-24. doi: 10.3969/j.issn.1000-7008.2012.01.006

    LAN Shanchao, WANG Hongfang, LI Wenbin. Finite element simulation and analysis of influence of grain size on wear of electroplated CBN grinding wheel [J]. Tool Engineering,2012,46(1):21-24. doi: 10.3969/j.issn.1000-7008.2012.01.006
    AGNARD S, LIU Z H, HAZEL B. Material removal and wheel wear models for robotic grinding wheel profiling [J]. Procedia Manufacturing,2015,2:35-40. doi: 10.1016/j.promfg.2015.07.007
    AHRENS M, DAMM J, DAGEN M, et al. Estimation of dynamic grinding wheel wear in plunge grinding [J]. Procedia CIRP,2017,58:422-427. doi: 10.1016/j.procir.2017.03.247
    MIAO Q, DING W F, KUANG W J, et al. Tool wear behavior of vitrified microcrystalline alumina wheels in creep feed profile grinding of turbine blade root of single crystal nickel-based superalloy [J]. Tribology International,2020,145:106144. doi: 10.1016/j.triboint.2019.106144
    周生合, 王军, 吕玉山, 等. 磨粒有序排布的电镀CBN砂轮磨削表面粗糙度仿真 [J]. 工具技术,2015,49(5):98-100. doi: 10.3969/j.issn.1000-7008.2015.05.029

    ZHOU Shenghe, WANG Jun, LV Yushan, et al. Simulation of grinding surface roughness of electroplated CBN grinding wheel with pattern [J]. Tool Engineering,2015,49(5):98-100. doi: 10.3969/j.issn.1000-7008.2015.05.029
    MOHAMMAD R, JOSEPH L Z W. Simulation of workpiece surface roughness after flat grinding by electroplated wheel [J]. Procedia CIRP,2018,77:303-306. doi: 10.1016/j.procir.2018.09.021
    肖军民, 谢晋. 20CrMnTi高速外圆磨削试验研究及参数优化 [J]. 机床与液压,2015,43(11):56-58. doi: 10.3969/j.issn.1001-3881.2015.11.016

    XIAO Junmin, XIE Jin. Experimental research and parameters optimization of high-speed cylindrical grinding for 20CrMnTi [J]. Machine Tool and Hydraulics,2015,43(11):56-58. doi: 10.3969/j.issn.1001-3881.2015.11.016
    WANG Y Z, LIU Y, CHU X M, et al. Calculation model for surface roughness of face gears by disc wheel grinding [J]. International Journal of Machine Tools and Manufacture,2017,123:76-88. doi: 10.1016/j.ijmachtools.2017.08.002
    LING H, YANG C M, FENG S C, et al. Predictive model of grinding residual stress for linear guideway considering straightening history [J]. International Journal of Mechanical Sciences,2020,176:105536. doi: 10.1016/j.ijmecsci.2020.105536
    WANG Y Z, ZHANG W, LIU Y. Analysis model for surface residual stress distribution of spiral bevel gear by generating grinding [J]. Mechanism and Machine Theory,2018,130:477-490. doi: 10.1016/j.mechmachtheory.2018.08.027
    KUANG W J, MIAO Q, DING W F, et al. Residual stresses of turbine blade root produced by creep-feed profile grinding: three-dimensional simulation based on workpiece-grain interaction and experimental verification [J]. Journal of Manufacturing Processes,2021,62:67-79. doi: 10.1016/j.jmapro.2020.11.045
    雷瑛, 李达, 罗森怡. 磨削加工件表面残余应力测试及其线性回归预测分析 [J]. 工具技术,2021,55(10):19-23. doi: 10.3969/j.issn.1000-7008.2021.10.004

    LEI Ying, LI Da, LUO Senyi. Surface residual stress measurement and linear regression prediction analysis of grinding workpiece [J]. Tool Engineering,2021,55(10):19-23. doi: 10.3969/j.issn.1000-7008.2021.10.004
    ZHOU W H, TANG J Y, SHAO W. Study on surface generation mechanism and roughness distribution in gear profile grinding [J]. International Journal of Mechanical Sciences,2020,187:105921. doi: 10.1016/j.ijmecsci.2020.105921
    巩亚东, 苏志朋, 孙瑶, 等. 镍基单晶高温合金微磨削形貌仿真及实验研究 [J]. 东北大学学报(自然科学版),2020,41(7):949-954. doi: 10.12068/j.issn.1005-3026.2020.07.007

    GENG Yadong, SU Zhipeng, SUN Yao, et al. Morphology simulation and experimental study on micro-grinding of nickel-based single crystal superalloy [J]. Journal of Northeastern University (Natural Science),2020,41(7):949-954. doi: 10.12068/j.issn.1005-3026.2020.07.007
    XIAO Y L, WANG S L, MA C, et al. Numerical modeling of material removal mechanism and surface topography for gear profile grinding [J]. Journal of Manufacturing Processes,2022,76:719-739. doi: 10.1016/j.jmapro.2022.02.052
    杨磊, 李郝林, 迟玉伦. 基于自适应模糊神经网络的砂轮磨损评估 [J]. 轻工机械,2020,38(6):72-76.

    YANG Lei, LI Haolin, CHI Yulun. Wear evaluation of grinding wheel based on adaptive fuzzy neural network [J]. Light Industry Machinery,2020,38(6):72-76.
    苏史博, 毕果, 郑守红, 等. 基于LSTM和声发射的金刚石砂轮磨损状态识别 [J]. 组合机床与自动化加工技术,2021,8:169-172.

    SU Shibo, BI Guo, ZHENG Shouhong, et al. Identification of wear status of diamond grinding wheel based on LSTM and acoustic emission [J]. Modular Machine Tool and Automatic Manufacturing Technique,2021,8:169-172.
    张铁, 胡广, 陈首彦. 基于模糊自整定PID的力控制磨削实验研究 [J]. 现代制造工程,2016,9:121-125. doi: 10.3969/j.issn.1005-2895.2020.06.014

    ZHANG Tie, HU Guang, CHEN Shouyan. Experiment research on force control grinding based on fuzzy-PID [J]. Modern Manufacturing Engineering,2016,9:121-125. doi: 10.3969/j.issn.1005-2895.2020.06.014
    LI D W, YANG J X, ZHAO H, et al. Contact force plan and control of robotic grinding towards ensuring contour accuracy of curved surfaces [J]. International Journal of Mechanical Sciences,2022,227:107449. doi: 10.1016/j.ijmecsci.2022.107449
    王雨, 孙龙, 王玉伟, 等. 风电叶片打磨机器人柔性末端磨削力抗扰控制 [J]. 计算机仿真,2020,37(7):384-390. doi: 10.3969/j.issn.1006-9348.2020.07.076

    WANG Yu, SUN Long, WANG Yuwei, et al. Auto disturbance rejection control of the flexible end grinding force of a wind turbine blade grinding robot [J]. Computer Simulation,2020,37(7):384-390. doi: 10.3969/j.issn.1006-9348.2020.07.076
    MITROFANOV A, PARSHEVA K, NOSENKO V. Simulation of an artificial neural network for predicting temperature and cutting force during grinding using CAMQL [J]. Materials Today:Proceedings,2021,38:1508-1511. doi: 10.1016/j.matpr.2020.08.139
    HEININEN A, PROD’HON R, MOKHTARIAN H, et al. Finite element modelling of temperature in cylindrical grinding for future integration in a digital twin [J]. Procedia CIRP,2021,104:875-880. doi: 10.1016/j.procir.2021.11.147
    路建萍, 董涛, 侯丽雅. 基于神经网络的磨削温度在线监测预报系统 [J]. 南京理工大学学报,2000,24(3):273-276. doi: 10.14177/j.cnki.32-1397n.2000.03.019

    LU Jianping, DONG Tao, HOU Liya. On-line monitoring and forecasting system for grinding arc temperature based on artificial neural network [J]. Journal of Nanjing University of Science and Technology,2000,24(3):273-276. doi: 10.14177/j.cnki.32-1397n.2000.03.019
    PENG R T, TONG J W, TANG X Z, et al. Application of a pressurized internal cooling method in grinding Inconel 718: Modeling-simulation and testing-validation [J]. International Journal of Mechanical Sciences,2021,189:105985. doi: 10.1016/j.ijmecsci.2020.105985
    SHARMIN I, MOON M, TALUKDER S, et al. Impact of nozzle design on grinding temperature of hardened steel under MQL condition [J]. Materials Today:Proceedings,2021,38:3232-3237. doi: 10.1016/j.matpr.2020.09.717
    XU X P, YU Y Q, HUANG H. Mechanisms of abrasive wear in the grinding of titanium (TC4) and nickel (K417) alloys [J]. Wear,2003,255:1421-1426. doi: 10.1016/S0043-1648(03)00163-7
    CARAGUAY S J, BOARON A, WEINGAERTNER W L, et al. Wear assessment of microcrystalline and electrofused aluminum oxide grinding wheels by multi-sensor monitoring technique [J]. Journal of Manufacturing Processes,2022,80:141-151. doi: 10.1016/j.jmapro.2022.05.052
    郭维诚, 李蓓智, 杨建国, 等. 磨削过程信号监测与砂轮磨损预测模型构建 [J]. 上海交通大学学报,2019,53(12):1475-1481. doi: 10.16183/j.cnki.jsjtu.2019.12.010

    GUO Weicheng, LI Beizhi, YANG Jianguo, et al. Monitoring of grinding signals and development of wheel wear prediction model [J]. Journal of Shanghai Jiao Tong University,2019,53(12):1475-1481. doi: 10.16183/j.cnki.jsjtu.2019.12.010
    丁宁, 段景淞, 石建, 等. 基于声发射砂轮磨损监测系统的研究 [J]. 南京航空航天大学学报,2020,52(1):48-52. doi: 10.16356/j.1005-2615.2020.01.005

    DING Ning, DUAN Jingsong, SHI Jian, et al. Research on grinding wheel wear monitoring system based on acoustic emission [J]. Journal of Nanjing University of Aeronautics and Astronautics,2020,52(1):48-52. doi: 10.16356/j.1005-2615.2020.01.005
    XU L M, NIU M, ZHAO D, et al. Methodology for the immediate detection and treatment of wheel wear in contour grinding [J]. Precision Engineering,2019,60:405-412. doi: 10.1016/j.precisioneng.2019.09.006
    NGUYEN D T, YIN S H, TANG Q C, et al. Online monitoring of surface roughness and grinding wheel wear when grinding Ti-6Al-4V titanium alloy using ANFIS-GPR hybrid algorithm and Taguchi analysis [J]. Precision Engineering,2019,55:275-292. doi: 10.1016/j.precisioneng.2018.09.018
    尹国强, 王东, 关云匀, 等. 基于声发射监测的砂轮磨损实验 [J]. 东北大学学报(自然科学版),2022,43(8):1127-1133. doi: 10.12068/j.issn.1005-3026.2022.08.009

    YIN Guoqiang, WANG Dong, GUAN Yunyun, et al. Grinding wheel wear experiment based on acoustic emission [J]. Journal of Northeastern University (Natural Science),2022,43(8):1127-1133. doi: 10.12068/j.issn.1005-3026.2022.08.009
    MAHATA S, SHAKYA P, BABU N R. A robust condition monitoring methodology for grinding wheel wear identification using Hilbert Huang transform [J]. Precision Engineering,2021,70:77-91. doi: 10.1016/j.precisioneng.2021.01.009
    陈廉清, 郭建亮, 杨勋, 等. 基于进化神经网络的磨削粗糙度预测模型 [J]. 计算机集成制造系统,2013,19(11):2854-2863. doi: 10.13196/j.cims.2013.11.chenlianqing.2854.10.20131123

    CHEN Lianqing, GUO Jianliang, YANG Xun, et al. Grinding roughness prediction model based on evolutionary artificial neural network [J]. Computer Integrated Manufacturing Systems,2013,19(11):2854-2863. doi: 10.13196/j.cims.2013.11.chenlianqing.2854.10.20131123
    LI Y, LIU Y H, TIAN Y B, et al. Application of improved fireworks algorithm in grinding surface roughness online monitoring [J]. Journal of Manufacturing Processes,2022,74:400-412. doi: 10.1016/j.jmapro.2021.12.046
    GOPAN V, WINS K L D, SURENDRAN A. Integrated ANN-GA approach for predictive modeling and optimization of grinding parameters with surface roughness as the response [J]. Materials today:proceedings,2018,5(5):12133-12141. doi: 10.1016/j.matpr.2018.02.191
    ALI Y M, ZHANG L C. Estimation of residual stresses induced by grinding using a fuzzy logic approach [J]. Journal of Materials Processing Technology,1997,63(1-3):875-880. doi: 10.1016/S0924-0136(96)02742-2
    WANG P Z, HE Z S, ZHANG Y S, et al. Control of grinding surface residual stress of Inconel 718 [J]. Procedia Engineering,2017,174:504-511. doi: 10.1016/j.proeng.2017.01.174
    李峰, 李学崑, 融亦鸣. 强化感应加热辅助磨削Inconel718的残余应力主动调控 [J]. 机械工程学报,2018,3:216-226. doi: 10.3901/JME.2018.03.216

    LI Feng, LI Xuekun, RONG Yiming. Active control of the residual stress in Inconel718 grinding assisted by the strengthen induction heating [J]. Journal of Mechanical Engineering,2018,3:216-226. doi: 10.3901/JME.2018.03.216
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      沈阳化工大学材料科学与工程学院 沈阳 110142

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