对静压气体轴承的流场模型建立、刚度计算作了分析与探讨。采用计算流体动力学（CFD）软件对气体轴承的流场进行仿真，根据仿真结果，建立基于支持向量机（SVM）的气体轴承性能模型，根据该模型计算气体轴承的刚度。在此基础上建立气体轴承-转子的有限元模型，利用有限元软件ANSYS对转子系统进行了模态分析。在考虑轴承刚度随供气压力和转速的变化下，计算转子系统的临界转速。结果表明该转子系统一、二阶临界转速对供气压力变化较为敏感，三阶临界转速不受此影响。该结果对静压气体轴承-转子系统中通过调整供气压力，避免在工作频率范围发生共振现象的产生有实际意义。
Abstract
The flow field model of the aerostatic bearing and calculation methods of bearing stiffness are established in this paper. The flow field model of the aerostatic bearing is simulated by Computational fluid dynamics (CFD) software. According to the simulation results. Bearing stiffness model is derived with support vector machine(SVM). Based on this, the finite element model of bearing-rotor is established. The aerostatic bearing rotor system is analyzed by the use of the finite element software ANSAY. The Critical speed of the aerostatic bearing rotor system related to the bearing supply gas pressure and rotor speed is determined. The results show that first and second critical speed are sensitive to the bearing air pressure while the third one is not. The simulation and analysis above may be helpful for preventing the aerostatic bearing rotor system from working on resonant area by adjusting the bearing supply gas pressure.
关键词
静压气体轴承 /
支持向量机 /
轴承供气压力 /
有限元分析 /
临界转速
{{custom_keyword}} /
Key words
aerostatic bearing /
support vector machine /
bearing supply gas pressure /
finite element analysis /
critical speed;
{{custom_keyword}} /
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 王云飞. 气体润滑理论与气体轴承设计[M]. 机械工业出版社, 1999.
WANG Yun-fei. Gas lubrication theory and gas bearing design [M]. Machinery Industry Press, 1999.
[2] Belforte G, Raparelli T, Viktorov V. Theoretical Investigation of Fluid Inertia Effects and Stability of Self-Acting Gas Journal Bearings[J]. Journal of Tribology. 1999, 121(4): 836-843.
[3] 王学敏，杜建军，李姗姗. 基于有限差分法对不同润滑介质下静压气体轴颈轴承性能研究[J]. 机械工程学报. 2012(03): 121-127.
WANG Xue-min, Du Jian-jun, Li Sha-shan. Performance Research on the Externally Pressurized Gas Journal Bearing under Different Working Gas Based on Finite Difference Method [J] . Journal of Mechanical Engineering. 2012 (03): 121-127.
[4] 李健，李青，李晓明. 静压气体轴承承载特性的数值计算研究?[J]. 润滑与密封. 2016, 41(12): 1-5.
Li Jian, Li Qing, Li Xiao-ming. Numerical Simulation Analysis on Load Capacity Characteristic of Aerodynamic Journal Bearing [J]. Lubrication and Seal. 2016, 41 (12): 1-5
[5] 赵广，刘盼年，于贺春，等. 静压气体轴承气膜力及其与转子耦合动力学特性研究[J]. 航空动力学报. 2012, 27(2): 472-480.
ZHAO Guang, Liu Pan-nian, Yu He-chun, et al. Research on gas film force of aerostatic gas bearing and its coupled dynamics with rotor [J] . Journal of Aerospace Power, 2012, 27 (2): 472-480.
[6] 韩东江，杨金福，陈昌婷，等. 轴承供气压力对静压气体轴承-转子系统动力学特性影响的实验[J]. 推进技术. 2014, 35(9): 1265-1270.
Han Dong-jiang, Yang Jin-fu, Chen Chang-ting, et al. Experimental Research for Effects of Bearing Supply Gas Pressure on Aerostatic Bearing-rotor System Dynamic Characteristics
[J]. Journal of Propulsion Technology. 2014, 35 (9): 1265-1270.
[7] Quiñonez A F, Morales-Espejel G E. Surface roughness effects in hydrodynamic bearings[J]. Tribology International. 2016, 98: 212-219.
[8] Zhu J, Chen H, Chen X. Large eddy simulation of vortex shedding and pressure fluctuation in aerostatic bearings[J]. Journal of Fluids & Structures. 2013, 40(7): 42-51.
[9] Eleshaky M E. CFD investigation of pressure depressions in aerostatic circular thrust bearings[J]. Tribology International. 2009, 42(7): 1108-1117.
[10] 张恩龙. 高速全支承气体静压电主轴的承载特性研究[D]. 广东工业大学, 2005.
ZHANG En-long. Research on bearing characteristics of high-speed full-support gas hydrostatic spindle [D] .Guangdong University of Technology, 2005.
[11] 刘海艳. 高速静压气体轴承—转子系统稳定性研究[D]. 大连海事大学, 2012.
LIU Hai-yan. Study on Stability of High Speed Hydrostatic Bearing / Rotor System [D]. Dalian Maritime University, 2012.
[12] Zhao M, Fu C, Ji L, et al. Feature selection and parameter optimization for support vector machines[J]. Expert Systems with Applications. 2011, 38(5): 5197-5204.
[13] Wang X, Chung F L, Wang S. Theoretical analysis for solution of support vector data description[J]. Neural Networks. 2011, 24(4): 360.
[14] 王维刚，刘占生. 多目标粒子群优化的支持向量机及其在齿轮故障诊断中的应用[J]. 振动工程学报. 2013, 26(5): 743-750.
WANG Wei-gang, LIU Zhan-sheng. Support vector machine optimized by multi-objective particle searm and application in gear fault diagnosis [J] . Journal of Vibration Engineering,
2013，26 (5):743-749.
[15] 姜万录，吴胜强. 基于SVM和证据理论的多数据融合故障诊断方法[J]. 仪器仪表学报. 2010, 31(8): 1738-1743.
JIAN Wan-lu，WU Sheng-qiang. Multi-data fusion fault diagnosis method based on SVM and evidence theory [J] . Chinese Journal of Scientific Instrument,2010，31 (8):1738-1743.
[16] 王正. 转动机械的转子动力学设计[M]. 清华大学出版社, 2015.
Wang Zheng. Rotating machinery rotor dynamics design [M]. Tsinghua University Press, 2015.
{{custom_fnGroup.title_cn}}
脚注
{{custom_fn.content}}
PDF(1170 KB)
