基于神经网络建模的机床滑动结合面动态特性参数识别

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振动与冲击 ›› 2018, Vol. 37 ›› Issue (7) : 109-115.

论文

朱坚民，周亚南，何丹丹，郑洲洋

作者信息 +

Dynamic characteristic parameters identification for machine tool sliding joints based on neural network modeling

ZHUJianmin, ZHOU Yanan, HEDandan, ZHENGZhouyang

Author information +

文章历史 +

摘要

针对机床滑动结合面动态特性参数难以准确确定的问题，以结合面的刚度参数、阻尼参数为优化变量，建立滑动结合面动态特性参数的神经网络模型，结合神经网络模型的计算结果与机床整机实验模态的分析结果，采用布谷鸟优化算法对结合面的刚度与阻尼参数进行优化识别。以自行设计制造的机床滑动结合面实验台上工作台与床身间的滑动导轨结合面为实例进行了建模、实验、参数识别等分析，分析结果表明：本文方法是可行的、有效的，参数识别精度高于已有文献研究。

Abstract

Aiming at the problem that dynamic characteristic parameters of sliding joints of a machine tool are difficult to identify accurately, here, a neural network modeling method for identifying sliding joints’ dynamic characteristic parameters was proposed. The model’s variables to be optimized were stiffness parameters and damping ones of sliding joints. With the calculation results of the neural network model and those of the machine tool test modal analysis, stiffness and damping parameter identification of the sliding joints was performed with the cuckoo optimization algorithm. As an example, modeling, tests and parametric identification were conducted for a self-designed and manufactured sliding guide joints between the working platform and the machine tool body. The results showed that the proposed method is feasible and effective; the parametric identification accuracy is higher than those recorded in literatures.

导出引用

朱坚民，周亚南，何丹丹，郑洲洋. 基于神经网络建模的机床滑动结合面动态特性参数识别[J]. 振动与冲击, 2018, 37(7): 109-115

ZHUJianmin, ZHOU Yanan, HEDandan, ZHENGZhouyang. Dynamic characteristic parameters identification for machine tool sliding joints based on neural network modeling[J]. Journal of Vibration and Shock, 2018, 37(7): 109-115

参考文献

[1] 赵宏林，丁庆新，曾鸣，等. 机床结合部特性的理论解析及应用[J]. 机械工程学报，2008, 44(12): 208-214.
Zhao Honglin, Ding Qingxin, Zeng Ming, et al. Theoretic Analysis on and Application of Behaviors of Machine Tool Joints [J]. Chinese Journal of Mechanical Engineering, 2008, 44(12): 208-214.
[2] Burdekin M, Back N, Cowley A. Analysis of the local deformation in machine joints [J]. ARCHIVE: Journal of Mechanical Engineering Science, 1979, 21: 25-32.
[3] Vafaei S, Rahnejat H, Aini R. Vibration monitoring of high speed spindles using spectral analysis techniques [J]. International Journal of Machine Tools & Manufacture, 2002, 42(11): 1223-1234.
[4] 李玲，蔡安江，蔡力钢. 栓接结合部动态特性参数辨识新方法[J]. 振动与冲击，2014, 33(14): 15-19.
Li Ling, CaiAnjiang, CaiLigang. New method to identify dynamic characteristics of bolted joints [J]. Journal of Vibration and Shock, 2014, 33(14): 15-19.
[5] 刘耀，黄玉美. 机床滚珠导轨中圆柱面-球面结合面静特性分析及试验研究[J].机械工程学报，2013, 49(21): 25-30.
Liu Yao, Huang Yumei. Theoretical analysis and experimental study on static characteristics of the cylindrical-spherical joint surfaces of linear ball guide on machine tool [J]. Chinese Journal of Mechanical Engineering, 2013, 49(21): 25-30.
[6] Edward Chlebus, Bogdan Dybala. Modeling and calculation of properties of sliding guideway [J]. International Journal of Machine Tools and Manufacture, 1999, 39(12): 1823-1839.
[7] 王禹林，吴晓枫，冯虎田. 基于结合面的大型螺纹磨床整机静动态特性优化[J]. 振动与冲击，2012, 31(20): 147-152.
Wang Yulin, Wu Xiaofeng, Feng Hutian. Static and dynamic characteristics optimization for a whole large-sized thread grinder based on joint surface [J]. Journal of Vibration and Shock, 2012, 31(20): 147-152.
[8] 郭成龙，袁军堂，汪振华，等.贴塑导轨结合面法向动态特性参数的识别及分析[J].振动与冲击，2013, 32(3): 95-98.
GuoChenglong, Yuan Juntang, Wang Zhenhua, et al. Identification and analysis for dynamic characteristic parameters of a plastic-coated guide’s joint [J]. Journal of Vibration and Shock, 2013, 32(3): 95-98.
[9] 伍良生，王泽林，屈重年，等.滑动结合面动态特性测试系统设计[J].机械设计与制造，2012(7): 9-11.
Wu Liangsheng, Wang Zelin, Qu Chongnian, et al. Design of dynamic characteristic testing system for sliding joint[J]. Machinery Design & Manufacture, 2012(7): 9-11.
[10] Lee W J, Kim S I. Joint stiffness identification of an ultra-precision machine for machining large-surface micro-feature[J]. International Journal of Precision Engineering and Manufacturing, 2009, 10(5): 115-121.
[11] 王立华，罗建平，刘泓滨，等.铣床关键结合面动态特性研究[J].振动与冲击，2008, 28(8): 125-129.
Wang Lihua, Luo Jianping, Liu Hongbin, et al. Research on dynamic characteristics of key machine joint surfaces of the numerically controled milling machine[J]. Journal of Vibration and Shock, 2008, 28(8): 125-129.
[12] 孙明楠，米良，干净，等.数控机床导轨结合部动态特性参数优化识别方法研究[J].四川大学学报（工程科学版），2012, 44(3): 217-223.
Sun Mingnan, Mi Liang, Gan Jing, et al. An optimum identification method of dynamic characteristic parameters of guideway joint on a NC machine tool[J]. Journal of Sichuan University(Engineering Science Edition), 2012, 44(3): 217-223.
[13] Deng Congying, Yin Guofu, Fang Hui, et al. Dynamic characteristics optimization for a whole vertical machining center based on the configuration of joint stiffness[J]. International Journal of Advanced Manufacturing Technology, 2015, 76(5-8):1225-1242.
[14]汪中厚，袁可可，李刚. 基于响应面法的滑动结合面动态特性参数优化识别[J]. 中国机械工程，2016, 27(5): 622-626.
Wang Zhonghou, Yuan Keke, Li Gang. Optimization identification for dynamic characteristic parameters of sliding joints based on response surface methodology[J]. China Mechanical Engineering, 2016, 27(5): 622-626.
[15] Yang X, Deb S. Cuckoo search via Lévy flights[C]. World Congress on Nature & Biologically Inspired Computing. Piscataway:IEEE Publications, 2009: 210-214.
[16] 廖伯瑜，周新民，尹志宏. 现代机械动力学及其工程应用[M]. 北京：机械工业出版社，2004.
Liao Boyu, Zhou Xinmin, Yin Zhihong. Modern mechanical dynamics and its engineering application [M]. Beijing: Machinery Industry Press, 2004.
[17] 李松，刘力军，解永乐.遗传算法优化BP神经网络的短时交通流混沌预测[J]. 控制与决策，2011, 26(10): 1581-1585.
Li Song, Liu Lijun, XieYongle. Chaotic prediction for short-term traffic flow of optimized BP neural network based on genetic algorithm [J]. Control and Decision, 2011, 26(10): 1581-1585.