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乏信息多传感器压力数据自助模糊融合估计

王中宇 王倩 付继华

王中宇, 王倩, 付继华等 . 乏信息多传感器压力数据自助模糊融合估计[J]. 北京航空航天大学学报, 2013, 39(11): 1426-1430.
引用本文: 王中宇, 王倩, 付继华等 . 乏信息多传感器压力数据自助模糊融合估计[J]. 北京航空航天大学学报, 2013, 39(11): 1426-1430.
Wang Zhongyu, Wang Qian, Fu Jihuaet al. Pressure multi-sensor data fusion and estimation of poor information based on bootstrap-fuzzy method[J]. Journal of Beijing University of Aeronautics and Astronautics, 2013, 39(11): 1426-1430. (in Chinese)
Citation: Wang Zhongyu, Wang Qian, Fu Jihuaet al. Pressure multi-sensor data fusion and estimation of poor information based on bootstrap-fuzzy method[J]. Journal of Beijing University of Aeronautics and Astronautics, 2013, 39(11): 1426-1430. (in Chinese)

乏信息多传感器压力数据自助模糊融合估计

基金项目: 技术基础科研资助项目(J132012C001);国家自然科学基金资助项目(50908215)
详细信息
  • 中图分类号: C37

Pressure multi-sensor data fusion and estimation of poor information based on bootstrap-fuzzy method

  • 摘要: 乏信息多传感器压力测量数据的融合估计是压力测量研究的重要问题,不同于经典的统计学方法,结合自助法和模糊数学的相关算法,提出一种实现乏信息多传感器压力测量数据融合估计的自助模糊数学模型.对具有乏信息特征的多个压力传感器的测量数据进行自助抽样;利用最大熵算法构建出不同时刻与位置的多个压力传感器测量数据的自助分布;用自助分布进行加权均值计算,提取相应特征值,得到自助融合序列;通过模糊隶属函数得到所测压力值的真值与区间估计.实例计算表明:在乏信息条件下,算法精度可达87%;在大样本条件下,测量数据在置信水平99.7%下,融合估计可靠性可达95%,验证了乏信息自助模糊融合估计算法的有效性.

     

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出版历程
  • 收稿日期:  2013-01-04
  • 网络出版日期:  2013-11-30

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