锻压技术

基于交互作用的超声滚挤压轴承套圈加工参数优化

英文标题：Optimization on machining parameters for ultrasonic rolling extrusion bearing rings based on interaction

作者：付浩然徐红玉王晓强田英健

分类号：TG376.1

出版年,卷(期):页码：2023,48(7):115-122

摘要：

以42CrMo钢为研究对象进行超声滚挤压正交试验，实现加工参数的优化控制。利用基于熵权理论建立的加工参数与表层性能之间的隶属函数评价关系，分析了加工参数对表层性能的显著性；根据交互作用最大隶属度原则，分析了加工参数间的交互作用，得出最优加工参数组合，并通过建立指数回归模型进行验证。结果表明：加工参数对表层性能的影响程度依次为：进给速度>静压力>振幅>转速；进给速度与静压力之间的交互作用的影响最大，进给速度与振幅、振幅与静压力次之，转速与进给速度、振幅、静压力的影响最小；最优加工参数为转速为550 r·min-1、进给速度为55 mm·min-1、振幅为5 μm、静压力为480 N，对比验证误差均控制在5%以下，实现了表层性能的全局最优。

For 42CrMo steel, the orthogonal experiments of ultrasonic rolling extrusion were conducted to achieve the optimal control of machining parameters, and the significance of machining parameters on surface performance was analyzed using affiliation function evaluation relationship between machining parameters and surface performance established by the entropy weight theory. Then, according to the principle of maximum affiliation degree of interaction, the interaction among machining parameters was analyzed to obtain the optimal combination of machining parameters, and the results were verified by establishing an exponential regression model. The results show that the degree of influence for machining parameters on surface performance is as follows: feed speed>static pressure>amplitude>rotational speed. The interaction between feed speed and static pressure has the greatest influence, followed by feed speed and amplitude, amplitude and static pressure, and the influence of rotational speed and feed speed, amplitude and static pressure is the smallest. The optimal machining parameters are the rotation speed of 550 r·min-1, the feed speed of 55 mm·min-1, the amplitude of 5 μm and the static pressure of 480 N, and the comparison verification errors are controlled below 5%, which realizes the global optimization of surface performance.

基金项目：

国家自然科学基金资助项目(U1804145); 国家重点研究计划（2018YFB2000405）

作者简介：付浩然(1995-)，男，硕士研究生 E-mail：1375525941@qq.com 通信作者：徐红玉（1972-），男，博士，教授 E-mail：xuhongyu@haust.edu.cn

参考文献：

[1]巩立超, 潘永智, 刘彦杰, 等. 超声滚压轴承套圈表面强化的研究综述[J]. 表面技术，2022,51(8):203-213.

Gong L C, Pan Y Z, Liu Y J, et al. Summary of research on surface strengthening of ultrasonic rolling bearing rings [J]. Surface Technology，2022,51(8):203-213.

[2]张建斌, 马勤, 季根顺, 等. 表面机械强化工业纯钛疲劳性能的研究[J]. 航空材料学报, 2001, (3): 46-50.

Zhang J B, Ma Q, Ji G S, et al. Study on fatigue properties of surface mechanical strengthening industrial pure titanium [J]. Journal of Aeronautical Materials, 2001,(3): 46-50.

[3]陶思伟, 张鑫. 20CrMnTi钢有无稀土渗碳热处理表面强化层的组织及性能研究[J]. 中国金属通报, 2021,(1): 211-212.

Tao S W, Zhang X. Study on microstructure and properties of surface strengthening layer of 20CrMnTi steel with or without rare earth carburizing heat treatment [J]. China Metal Bulletin, 2021, (1): 211-212.

[4]徐庆泽, 蔡晋, 孟庆勋, 等. 喷丸强化对电火花加工表面影响的研究进展[J]. 航空精密制造技术, 2020, 56(5): 1-5,25.

Xu Q Z, Cai J, Meng Q X, et al. Research progress on the effect of shot peening on EDM surface [J]. Aviation Precision Manufacturing Technology, 2020, 56 (5): 1-5,25.

[5]金江, 刘燕, 王艺. 用于铝合金零件表面强化的NiSiO2MoS2复合镀层的研究[J]. 电镀与环保, 2019, 39(1): 10-12.

Jin J, Liu Y, Wang Y. Research on NiSiO2MoS2 composite coating for surface strengthening of aluminum alloy parts [J]. Electroplating & Pollution Control, 2019, 39 (1): 10-12.

[6]Wang N, Zhu J L, Liu B, et al. Influence of ultrasonic surface rolling process and shot peening on fretting fatigue performance of Ti6Al4V [J]. Chinese Journal of Mechanical Engineering, 2021, 34(6): 63-75.

[7]王晓强, 荣莎莎, 刘佳, 等. 超声滚挤压轴承套圈表面粗糙度响应曲面预测模型[J]. 塑性工程学报, 2018, 25(3):54-59.

Wang X Q, Rong S S, Liu J, et al. Surface roughness response prediction model of ultrasonic roll extrusion bearing ring [J]. Journal of Plasticity Engineering, 2018, 25(3):54-59.

[8]徐红玉, 黄焱燚, 崔凤奎. 超声滚挤压轴承套圈表层残余应力模型[J]. 塑性工程学报, 2018, 25(5):205-211.

Xu H Y, Huang Y Y, Cui F K, et al. Residual stress model of bearing ring surface by ultrasonic rolling extrusion [J]. Journal of Plastic Engineering, 2018, 25 (5): 205-211.

[9]王晓强, 阮孝林, 崔凤奎, 等. 超声滚挤压表面硬度预测模型研究[J]. 机械强度, 2020, 42(4): 811-816.

Wang X Q, Ruan X L, Cui F K, et al. Study on prediction model of surface hardness of ultrasonic roll extrusion [J]. Journal of Mechanical Strength, 2020, 42 (4): 811-816.

[10]崔凤奎, 苏涌翔, 荣莎莎, 等. 超声滚挤压轴承套圈表面粗糙度数学模型对比分析[J]. 塑性工程学报, 2018, 25(5):199-204.

Cui F K, Su Y X, Rong S S, et al. Comparative analysis of mathematical model for surface roughness of ultrasonic rolling extrusion bearing rings [J]. Journal of Plasticity Engineering, 2018, 25(5):199-204.

[11]苏涌翔. 超声滚挤压轴承套圈表面完整性研究[D]. 洛阳：河南科技大学, 2019.

Su Y X. Study on Surface Integrity of Bearing Ring by Ultrasonic Rolling Extrusion [D]. Luoyang: Henan University of Science and Technology, 2019.

[12]陈捡, 刘飞, 王晓强. 超声滚挤压强化7050铝合金的表面粗糙度[J]. 锻压技术, 2021, 46(12):148-153.

Chen J, Liu F, Wang X Q. Surface roughness of 7050 aluminum alloy strengthened by ultrasonic rolling extrusion [J]. Forging & Stamping Technology, 2021, 46(12):148-153.

[13]朱其萍, 徐红玉, 王晓强, 等. 基于PSOBP的超声滚挤压轴承套圈表面加工硬化程度预测[J]. 锻压技术, 2021, 46(11): 190-196.

Zhu Q P, Xu H Y, Wang X Q, et al. Prediction of surface work hardening degree of ultrasonic rolling extrusion bearing rings based on PSOBP [J]. Forging & Stamping Technology, 2021, 46(11): 190-196.

[14]刘志飞, 王晓强, 朱其萍, 等. 超声滚挤压轴承套圈的表层性能预测模型建立及工艺参数优化[J].锻压技术,2021,46(3):118-125.

Liu Z F, Wang X Q, Zhu Q P, et al. Establishment of surface performance prediction model and optimization of process parameters for bearing rings by ultrasonic roll extrusion [J]. Forging & Stamping Technology, 2021,46 (3): 118-125.

[15]程明龙, 肖勇, 刘康宁, 等. 超声振动滚挤压对金属表面微观组织的影响[J]. 工具技术, 2019, 53(7):73-76.

Cheng M L, Xiao Y, Liu K N, et al. Effect of ultrasonic vibration rolling extrusion on Microstructure of metal surface [J]. Tool Engineering, 2019, 53 (7): 73-76.

[16]张甜, 阎红灿. 基于熵权法的多属性决策算法优化及应用[J]. 华北理工大学学报: 自然科学版, 2022, 44(1): 82-88.

Zhang T, Yan H C. Optimization and application of multiattribute decisionmaking algorithm based on entropy weight method [J]. Journal of North China University of Science and Technology: Natural Science Edition, 2022, 44(1): 82-88.

[17]朱常安, 胡文华, 郭宝峰, 等. 基于熵权法和组合隶属函数的雷达质量评估方法研究[J]. 计算机测量与控制, 2022, 30(6): 302-307.

Zhu C A, Hu W H, Guo B F, al. Research on radar quality assessment method based on entropy weight method and combined membership function [J]. Computer Measurement & Control, 2022, 30(6): 302-307.

[18]余婷, 裴莉莉, 李伟, 等. 基于随机森林算法的路面状况指数预测[J]. 公路交通科技, 2021, 38(10): 16-23.

Yu T, Pei L L, Li W, et al. Prediction of pavement condition index based on random forest algorithm [J]. Journal of Highway and Transportation Research and Development, 2021, 38(10): 16-23.

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