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Chin J Eng Design  2022, Vol. 29 Issue (6): 739-747    DOI: 10.3785/j.issn.1006-754X.2022.00.081
Design for Quality     
Transmission accuracy reliability analysis and parameter optimization of RV reducer considering cycloid gear wear
Jiang LIU1(),Zheng-ming XIAO1(),Long-long ZHANG1,Wei-biao LIU2
1.School of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China
2.Yunnan Kunming Iron & Steel Heavy Equipment Manufacturing Group Co. , Ltd. , Kunming 650501, China
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Abstract  

In view of the problem that the transmission accuracy of RV (rotate vector) reducer decreased due to the wear of its parts in the working process, a dynamic reliability model of the transmission accuracy of RV reducer considering the wear of cycloid wheel was established, the reliability of transmission accuracy was analyzed, and the tolerance of key parts and the modification parameters of cycloid wheel were optimized. Taking a heavy-load RV reducer as the research object, the wear depth of cycloidal gear was calculated by using Archard wear formula, the distribution of gear tooth profile wear was analyzed, and the wear amount was predicted by using Gaussian process regression model based on numerical simulation data; the reliability model of RV reducer transmission accuracy with dynamic wear was established, and its dynamic reliability was solved by Monte Carlo method; an optimization model was established with the dynamic reliability of transmission accuracy as the constraint condition, the minimum machining cost and the minimum maximum wear in the rated life cycle as the optimization objectives, and the optimal solution was obtained adopting multi-objective genetic algorithm. The results showed that after optimization, the wear of cycloidal gear was slightly increased, and the machining cost of reducer was obviously reduced; the reliability of transmission accuracy of the reducer had been significantly improved, and the reliability within the rated life of 6 000 h met expected requirements. The research results can provide reference for the design of high-precision RV reducer.



Key wordsRV (rotate vector) reducer      cycloidal gear wear      transmission accuracy      dynamic reliability      multi-objective optimization     
Received: 25 February 2022      Published: 06 January 2023
CLC:  TH 132.46  
Corresponding Authors: Zheng-ming XIAO     E-mail: 1695898727@qq.com;suzem@sina.com
Cite this article:

Jiang LIU,Zheng-ming XIAO,Long-long ZHANG,Wei-biao LIU. Transmission accuracy reliability analysis and parameter optimization of RV reducer considering cycloid gear wear. Chin J Eng Design, 2022, 29(6): 739-747.

URL:

https://www.zjujournals.com/gcsjxb/10.3785/j.issn.1006-754X.2022.00.081     OR     https://www.zjujournals.com/gcsjxb/Y2022/V29/I6/739


考虑摆线轮磨损的RV减速器传动精度可靠性分析与参数优化

针对RV (rotate vector)减速器在工作过程中存在的零件磨损导致传动精度下降的问题,建立了考虑摆线轮磨损的RV减速器传动精度动态可靠性模型,进行传动精度可靠性分析,并对关键零件的公差以及摆线轮的修形参数进行优化设计。以某重载RV减速器为研究对象,利用Archard磨损公式对摆线轮的磨损深度进行计算,分析轮齿齿廓磨损的分布情况,并基于数值仿真数据利用高斯过程回归模型预测磨损量;建立了含动态磨损的RV减速器传动精度可靠性模型,用蒙特卡洛法求解其动态可靠度;建立了以传动精度动态可靠度为约束条件,以加工成本最低、额定寿命周期内最大磨损量最小为优化目标的优化模型,采用多目标遗传算法求得最优解。结果表明;优化后摆线轮的磨损量略微增大,而减速器的加工成本明显降低;优化后减速器传动精度可靠度得到明显提高,在额定寿命6 000 h内的可靠度满足预期要求。研究结果可以为高精度RV减速器的设计提供参考。


关键词: RV (rotate vector)减速器,  摆线轮磨损,  传动精度,  动态可靠度,  多目标优化 
参数数值参数数值
摆线轮齿数39移距修形量/mm-0.030
针齿数40弹性模量/GPa206
针齿半径/mm5泊松比0.3
针齿中心圆半径/mm114.5渐开线太阳轮分度圆半径/mm15
偏心距/mm2.2中心距/mm63
摆线轮齿宽/mm18渐开线齿轮压力角/(°)20
等距修形量/mm-0.026额定负载/(N·m)3 136
Table 1 Parameters of a RV reducer
Fig.1 Force on cycloidal gear with different modification amount
Fig.2 Wear amount of cycloidal gear with different modification amount
Fig.3 Comparison between simulation value and prediction value of cycloidal gear wear
序号j误差因素法向侧隙灵敏度指数
1公法线平均长度偏差Ew-Ewcosθ-0.037
2齿圈径向跳动误差Δfr2Δfrtanθ0.025
3中心距误差Δfa2Δfatanθ0.025
4等距修形量Δrrp2Δrrp1.56
5移距修形量Δrp-2Δrp1-K12-1
6针齿中心圆半径误差δrp2δrp1-K121
7针齿半径误差δrrp-2δrrp-1.56
8针齿销孔配合间隙δJδJ0.78
9摆线轮齿圈径向圆跳动误差ΔFr12ΔFr0.39
10针齿销孔圆周位置度δt2K1δt1.20
11摆线轮齿廓累积误差Fpk-K1Fpk-0.60
12等距修形误差δΔrrp2δΔrrp1.56
13移距修形误差δΔrp-2δΔrp1-K12-1
14偏心距误差δa2knδa0.00016
15摆线轮齿廓磨损δw2δw1.56
16曲柄轴承间隙ΔrΔr1.06
Table 2 Normal backlash caused by RV reducer error factor and sensitivity index of each error
参数数值

分布

特征

参数数值

分布

特征

Ew-0.049-0.086正态δt±0.005正态
Δfr0.014瑞利Fpk0.015正态
Δfa±0.01正态δΔrrp±0.001正态
δrp±0.0025正态δΔrp±0.002正态
δrrp-0.0075?-0.0087正态δa±0.002正态
δJ+0.010?+0.005正态Δr+0.004?+0.001正态
ΔFr0.009瑞利
Table 3 Deviation value and distribution characteristics of error term of RV reducer
Fig.4 Backlash simulation diagram of RV reducer
Fig.5 Variation curve of accuracy reliability of RV reducer with working time
参数下限值上限值参数下限值上限值
Δrrp-0.0530.011ΔFr0.0090.0017
Δrp-0.0570.007δt0.0050.009
δrp0.00250.005Fpk0.0150.030
δrrp-0.010-0.006δΔrrp0.0010.003
δJ0.0050.020δΔrp0.0010.003
Table 4 Value range of optimization parameters of RV reducer
Fig.6 Pareto frontal solution set for multi-objective optimization of RV reducer
参数优化1优化2参数优化1优化2
Δrrp-0.028 7-0.034 7ΔFr0.014 50.012 3
Δrp-0.032 7-0.038 7δt±0.008 5±0.007 9
δrp±0.004 5±0.004 1Fpk0.027 30.028 1
δrrp

-0.006 2

-0.008 2

-0.007 3

-0.008 4

δΔrrp±0.002 8±0.002 6
δJ

+0.013 0

+0.005 5

+0.015 1

+0.007 1

δΔrp±0.002 9±0.002 7
Table 5 Parameters of RV reducer after optimization
Fig.7 Comparison of transmission accuracy reliability of RV reducer before and after optimization
[10]   ZHANG Jun, BIAN Shi-yuan, LU Qing, et al. Quasi-static-model-based wear analysis of spur gears[J]. Journal of Mechanical Engineering, 2017, 53(5): 136-145.
doi: 10.3901/jme.2017.05.136
[11]   苏建新,李晨.RV减速器摆线轮磨损量的数值计算与分析[J].机械传动,2021,45(4):41-45,57.
SU Jian-xin, LI Chen. Numerical calculation and analysis of cycloidal gear wear amoun of RV reducer[J]. Journal of Mechanical Transmission, 2021, 45(4): 41-45, 57.
[12]   SHEN Xue-jin, LIU Yun-fei, CAO Lei, et al. Numerical simulation of sliding wear for self-lubricating spherical plain bearings[J]. Journal of Materials Research and Technology, 2012, 1(1): 8-12.
[13]   李聪波,何娇,杜彦斌,等.基于Archard模型的机床导轨磨损模型及有限元分析[J].机械工程学报,2016,52(15): 106-113. doi:10.3901/jme.2016.15.106
LI Cong-bo, HE Jiao, DU Yan-bin, et al. Archard model based machine tool wear model and finite element analysisl[J]. Journal of Mechanical Engineering, 2016, 52(15): 106-113.
doi: 10.3901/jme.2016.15.106
[14]   JANAKIRAMAN V, LI S, KAHRAMAN A. An investigation of the impacts of contact parameters on wear coefficient[J]. Journal of Tribology, 2014, 136(3): 031602-1)-(031602-7).
[15]   李威,胡岳龙.RV减速器摆线齿轮热分析[J].哈尔滨工程大学学报,2017,38(10):1560-1567. doi:10.11990/jheu.201605085
LI Wei, HU Yue-long. Thermal analysis of cycloidal gear for the RV reducer[J]. Journal of Harbin Engineering University, 2017, 38(10): 1560-1567.
doi: 10.11990/jheu.201605085
[16]   LEE K, CHO H, LEE I. Variable selection using Gaussian process regression-based metrics for high-dimensional model approximation with limited data[J]. Structural and Multidisciplinary Optimization, 2018, 59(5): 1439-1454.
[17]   刘勤,李娟,刘英.磨损随机过程建模及实例分析[J].兵工学报,2010,31(10):1379-1382.
LIU Qin, LI Juan, LIU Ying. Modeling and example analysis of wear random process[J]. Acta Armamentarii, 2010, 31(10): 1379-1382.
[1]   PHAM A D, AHN H J. High precision reducers for industrial robots driving 4th industrial revolution: state of arts, analysis, design, performance evaluation and perspective[J]. International Journal of Precision Engineering and Manufacturing: Green Technology, 2018, 5(4): 519-533.
[2]   YANG D C H, BLANCHE J G. Design and application guidelines for cycloid drives with machining tolerances [J]. Mechanism and Machine Theory, 1990, 25(5): 487-501.
[3]   BLANCHE J G, YANG D C H. Cycloid drives with machining tolerances[J]. Journal of Mechanisms, Transmissions, and Automation in Design, 1989, 111(3): 337-344.
[4]   任重义,毛世民,郭学东.RV减速器几何回差的精确建模及试验研究[J].机械科学与技术,2022,41(8):1216-1223.
REN Zhong-yi, MAO Shi-min, GUO Xue-dong. Research on accurate modeling and test of geometric backlash of RV reducer[J]. Mechanical Science and Technology for Aerospace Engineering, 2022, 41(8): 1216-1223.
[5]   LIN K S, CHAN K Y, LEE J J. Kinematic error analysis and tolerance allocation of cycloidal gear reducers[J]. Mechanism and Machine Theory, 2018, 124: 73-91.
[6]   曹代佳.RV减速器关键零部件公差设计方法研究[D]. 重庆:重庆大学,2018:43-53.
CAO Dai-jia. Research on tolerance design method for key components of RV reducer[D]. Chongqing: Chong-qing University, 2018: 43-53.
[7]   CHU Xu-yang, XU Hui-huang, WU Xiao-min, et al. The method of selective assembly for the RV reducer based on genetic algorithm[J]. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2017, 232(6): 921-929.
[8]   陆龙生,张飞翔,万珍平,等.基于回差优化的RV减速器摆线轮齿廓修形[J].华南理工大学学报(自然科学版),2018,46(9):1-8.
LU Long-sheng, ZHANG Fei-xiang, WAN Zhen-ping, et al. Cycloidal gear tooth profile modification of RV reducer based on backlash optimization[J]. Journal of South China University of Technology (Natural Science Edition), 2018, 46(9): 1-8.
[9]   ARCHARD J F. Contact and rubbing of flat surfaces [J]. Journal of Applied Physics, 1953, 24(8): 981-988.
[10]   张俊,卞世元,鲁庆,等.准静态工况下渐开线直齿轮齿面磨损建模与分析[J].机械工程学报,2017,53(5):136-145. doi:10.3901/jme.2017.05.136
doi: 10.3901/jme.2017.05.136
[18]   RASMUSSEN C E, WILLIAMS C K I. Gaussian processes for machine learning[M]. Cambridge: The MIT Press, 2006: 13-18.
[19]   王晓笋,巫世晶,周旭辉,等.含磨损故障的齿轮传动系统非线性动力学特性[J].振动与冲击,2013,32(16): 37-43,69. doi:10.3969/j.issn.1000-3835.2013.16.007
WANG Xiao-sun, WU Shi-jing, ZHOU Xu-hui, et al. Nonlinear dynamics analysis of gear transmission system with wear fault[J]. Journal of Vibration and Shock, 2013, 32(16): 37-43, 69.
doi: 10.3969/j.issn.1000-3835.2013.16.007
[20]   闻邦椿.机械设计手册:第2卷[M].北京:机械工业出版社, 2017:(9-114)-(9-137).
WEN Bang-chun. Handbook of mechanical design: Volume 2 [M]. Beijing: China Machine Press, 2017: (9-114)-(9-137).
[21]   潘柏松,方宽,文娟,等.考虑磨损与变形的谐波齿轮精度可靠性分析与优化设计[J].计算机集成制造系统,2022, 28(2):355-367.
PAN Bai-song, FANG Kuan, WEN Juan, et al. Accuracy reliability analysis and optimization design of harmonic gear considering wear and deformation[J]. Computer Integrated Manufacturing Systems, 2022, 28(2): 355-367.
[22]   钱华明.工业机器人关键部件的时变可靠性分析及优化方法研究[D].成都:电子科技大学,2021:3-10.
QIAN Hua-ming. Research on time-varying reliability analysis and optimization method for key components of industrial robots[D]. Chengdu: University of Electronic Science and Technology of China, 2021: 3-10.
[23]   高峰,刘秀婷,俞斌.非线性硬涂层整体叶盘振动参数的多目标优化设计[J].航空动力学报,2022,37(1):103-113.
GAO Feng, LIU Xiu-ting, YU Bin. Multi-objective optimization design for the vibration parameters of the nonlinear hard-coating blisk[J]. Journal of Aerospace Power, 2022, 37(1): 103-113.
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