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乏信息空间机械臂随机振动信号的灰自助评估

汪启跃,  王中宇,  王岩庆,  姚贞建

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文章导航 > 北京航空航天大学学报  > 2016 >  42(4): 858-864.
汪启跃, 王中宇, 王岩庆, 等 . 乏信息空间机械臂随机振动信号的灰自助评估[J]. 北京航空航天大学学报, 2016, 42(4): 858-864. doi: 10.13700/j.bh.1001-5965.2015.0270
引用本文: 汪启跃, 王中宇, 王岩庆, 等 . 乏信息空间机械臂随机振动信号的灰自助评估[J]. 北京航空航天大学学报, 2016, 42(4): 858-864. doi: 10.13700/j.bh.1001-5965.2015.0270
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WANG Qiyue, WANG Zhongyu, WANG Yanqing, et al. Estimation of space manipulator random vibration signals with poor information based on grey bootstrap method[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(4): 858-864. doi: 10.13700/j.bh.1001-5965.2015.0270(in Chinese)
Citation: WANG Qiyue, WANG Zhongyu, WANG Yanqing, et al. Estimation of space manipulator random vibration signals with poor information based on grey bootstrap method[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(4): 858-864. doi: 10.13700/j.bh.1001-5965.2015.0270(in Chinese)
shu

乏信息空间机械臂随机振动信号的灰自助评估

doi: 10.13700/j.bh.1001-5965.2015.0270
  • 1.

    北京航空航天大学仪器科学与光电工程学院, 北京 100083

  • 2. 中国科学院光电研究院, 北京 100094

基金项目: 航空科学基金(20100251006)
详细信息
    作者简介:

    汪启跃 男,硕士研究生。主要研究方向:精密测量技术与应用。 Tel.: 010-82339303 E-mail: wangqiyue9339@buaa.edu.cn;王中宇 男,博士，教授,博士生导师。主要研究方向:精密光机电技术一体化。 Tel.: 010-82338881 E-mail: mewan@buaa.edu.cn

    通讯作者:

    王中宇, Tel.: 010-82338881 E-mail: mewan@buaa.edu.cn

  • 中图分类号: V11

Estimation of space manipulator random vibration signals with poor information based on grey bootstrap method

  • 1.

    School of Instrumentation Science & Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

  • 2. Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing 100094, China

Funds: Aeronautical Science Foundation of China (20100251006)

    摘要
  • 摘要: 经典的统计学方法无法解决乏信息数据的评估问题。结合自助法和灰色系统理论,提出一种实现乏信息空间机械臂随机振动数据估计的灰自助方法。运用自助法对乏信息振动功率谱密度进行自助再抽样得到大量样本数据;利用灰色系统理论和最大熵理论建立灰自助模型,构建振动功率谱密度在不同频率点的灰自助分布。利用灰自助方法得到随机振动功率谱密度的真值估计和区间估计。提出了可靠度偏差和区间准确度2个指标对区间估计进行评价。灰自助方法与灰色方法和自助法的对比与测量实例表明,真值估计平均相对误差小于5%,在不同置信度水平下区间估计的准确度高于97%。

     

    Abstract: The classic statistical methods based on statistical theory can not solve the estimation of poor information data. A novel method based on grey bootstrap model for space manipulator random vibration signals with poor information was presented. The random vibration measurement data was processed by the bootstrap sampling．The bootstrap sequence was derived from the bootstrap distribution, and then the system theory was used to establish a bootstrap model. The true value and the interval of the space manipulator random vibration signals with poor information were estimated．grey bootstrap method is compared with grey method and bootstrap method. Experimental results show that grey bootstrap method has high accuracy. The validity of the proposed method is examined．The mean value of estimated relative errors are less than 5%, meanwhile, the estimated interval accuracy calculated with different confidence levels are more than 97%.

     

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出版历程
  • 收稿日期:  2015-04-29
  • 修回日期:  2015-06-26
  • 网络出版日期:  2016-04-20

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