全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
工程力学  2014 

基于SVM回归柔性机构的动态可靠性研究

DOI: 10.6052/j.issn.1000-4750.2013.06.0582, PP. 208-216

Keywords: 柔性机构,支持向量机回归,蒙特卡洛法,动态可靠性,SVM回归极值法

Full-Text   Cite this paper   Add to My Lib

Abstract:

在柔性机构(FlexibilityMechanism,FM)动态可靠性分析中,为了提高其计算精度和计算效率,通过融合蒙特卡洛和支持向量机回归理论,提出了一种新的SVM回归极值法(SVMRegressionExtremumMethod,SREM)。该方法借助ADAMS软件抽取FM动态响应极值的小样本,基于支持向量机回归理论建立FM动态响应极值的代理模型,使用此代理模型进行FM动态响应可靠性分析。最后,利用蒙特卡洛法、SVM回归极值法和另外两种方法对柔性曲柄摇杆机构的摇杆最大摆角可靠度进行分析。结果显示:在小样本情况下,SVM回归极值法的计算精度与MC相当,精度明显高于另外两种方法;SVM回归极值法的计算效率比MC大幅度提高,与另外两种方法计算效率相当。验证了在小样本情况下,SREM在FM动态可靠性分析中高效率和高精度。

References

[1]  张壮南, 王春刚, 等. 基于蒙特卡罗的考虑随机初始缺陷的分析方法[J]. 工程力学, 2013, 30(3): 476―480. Jin Lu, Zhang Zhuangnan, Wang Chungang, et al. Monte Carlo-based analysis method considering random initial imperfections [J]. Engineering Mechanics, 2013, 30(3): 476―480. (in Chinese)
[2]  H Z, Zhang H. Structural reliability assessment by local approximation of limit state functions using adaptive markov chain simulation and support vector regression [J]. Computer-Aided Civil and Infrastructure Engineering, 2012, 27: 676―686.
[3]  白广忱, 焦俊婷, 等. 柔性机构变形动态响应可靠性分析方法[J]. 宇航学报, 2006, 27(5): 1039―1043. Yu Linchong, Bai Guangchen, Jiao Junting, et al. Research on deformation dynamic response reliability analysis of flexible mechanism [J]. Journal of Astronautics, 2006, 27(5): 1039―1043. (in Chinese)
[4]  白广忱. 柔性机构运动参数动态可靠性分析方法研究 [J]. 机械传动, 2006, 30(4): 1―3. Yu Linchong, Bai Guangchen. Research on dynamical reliability analysis of flexible mechanism kinematical parameters [J]. Journal of Mechanical Transmission, 2006, 30(4): 1―3. (in Chinese)
[5]  白广忱, 焦俊婷, 等. 空间站展开机构虚拟样机仿真及可靠性分析[J]. 系统仿真学报, 2007, 19(1): 78―80. Yu Linchong, Bai Guangchen, Jiao Junting, et al. Virtual prototype simulation and reliability analysis of space station expand mechanism [J]. Journal of System Simulation, 2007, 19(1): 78―80. (in Chinese)
[6]  孙晓玲, 解大鹏. 基于LMI的随机神经网络全局渐进稳定性[J]. 淮阴师范学院学报, 2009, 8(3): 187―190. Wang Ning, Sun Xiaoling, Xie Dapeng. LMI-based approach for global asymptotic stability of stochastic neural networks [J]. Journal of Huaiyin Teachers College, 2009, 8(3): 187―190. (in Chinese)
[7]  Chunyi, Bai Guangchen. Reliability analysis on two-link flexible robot manipulator [C]// Piscataway United States: IEEE Computer Society, 2010: 2269―2272.
[8]  白广忱, 向敬忠. 基于极值响应面法的柔性机构可靠性优化设计[J]. 哈尔滨工程大学学报, 2010, 31(11): 1503―1507. Zhang Chunyi, Bai Guangchen, Xiang Jingzhong. Optimized reliability design for flexible mechanisms based on the extremum response surface method [J]. Journal of Harbin Engineering University, 2010, 31(11): 1503―1507. (in Chinese)
[9]  靳其兵, 曹柳林. 面向多输入输出系统的支持向量机回归[J]. 清华大学学报, 2007, 47(2): 1737―1741. Wang Jing, Jin Qibing, Cao Liulin. Support vector regression algorithm for multi-input multi-output systems [J]. Journal Of Tsinghua University, 2007, 47(2): 1737―1741. (in Chinese)
[10]  吕震宙. 基于支持向量机回归的结构系统可靠性及灵敏度分析方法[J]. 固体力学学报, 2007, 28(4): 415―419. Ma Chao, Lü Zhenzhou. Structural system reliability and sensitivity analysis based on support vector machine regression [J]. Acta Mechanica Solida Sinica, 2007, 28(4): 415―419. (in Chinese)
[11]  杨自春. 结构非概率可靠性分析的支持向量机分类方法[J]. 工程力学, 2012, 29(4): 150―154. Sun Wencai, Yang Zichun. Support vector classification for structural non-probabilistic reliability analysis [J]. Engineering Mechanics, 2012, 29(4): 150―154. (in Chinese)
[12]  程文明, 程跃. 基于支持向量机回归的结构可靠性分析[J]. 机械科学与技术, 2011, 30(1): 52―56. Zheng Yan, Cheng Wenming, Cheng Yue. Structural reliability analysis based on support vector regression [J]. Mechanical Science and Technology for Aerospace Engineering, 2011, 30(1): 52―56. (in Chinese)
[13]  吕震宙, 许鑫. 基于马尔科夫链模拟的支持向量机可靠性分析方法[J]. 工程力学, 2011, 28(2): 36―43. Yuan Xiukai, Lu Zhenzhou, Xu Xin. Support vector machine reliability analysis method based on Markov chain simulation [J]. Engineering Mechanics, 2011, 28(2): 36―43. (in Chinese)

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133