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连续变迎角试验数据自适应分段拟合滤波方法

王南天 王雄 孙鹏 许晓斌 邹琼芬

王南天, 王雄, 孙鹏, 等 . 连续变迎角试验数据自适应分段拟合滤波方法[J]. 北京航空航天大学学报, 2021, 47(6): 1145-1151. doi: 10.13700/j.bh.1001-5965.2020.0145
引用本文: 王南天, 王雄, 孙鹏, 等 . 连续变迎角试验数据自适应分段拟合滤波方法[J]. 北京航空航天大学学报, 2021, 47(6): 1145-1151. doi: 10.13700/j.bh.1001-5965.2020.0145
WANG Nantian, WANG Xiong, SUN Peng, et al. Self-adaptive piecewise fitting filtering method for test data in continuous sweeping angle of attack[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(6): 1145-1151. doi: 10.13700/j.bh.1001-5965.2020.0145(in Chinese)
Citation: WANG Nantian, WANG Xiong, SUN Peng, et al. Self-adaptive piecewise fitting filtering method for test data in continuous sweeping angle of attack[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(6): 1145-1151. doi: 10.13700/j.bh.1001-5965.2020.0145(in Chinese)

连续变迎角试验数据自适应分段拟合滤波方法

doi: 10.13700/j.bh.1001-5965.2020.0145
详细信息
    通讯作者:

    王南天. E-mail: wangnant@126.com

  • 中图分类号: V216.1

Self-adaptive piecewise fitting filtering method for test data in continuous sweeping angle of attack

More Information
  • 摘要:

    针对常用的阶梯变迎角数据处理方法处理连续变迎角试验数据时,不能去除低频振动分量的问题,基于试验数据中的近似对称、局部线性等特点,提出一种将数据进行分段二项式拟合的处理方法,并详细论述其基本原理,重点介绍基于方差极小值动态确定数据分段长度的方法。基于测试信号的实验结果表明所提方法可将低频分量信号滤除近70%,有效提高数据处理精度。经标模试验测试验证,所提方法可成功应用于某些试验。

     

  • 图 1  连续变迎角试验数据及其功率谱

    Figure 1.  Data of continuous sweeping angle of attack test and its power spectrum

    图 2  振动数据误差特性

    Figure 2.  Error characteristics of vibration data

    图 3  方法实现步骤

    Figure 3.  Implementation steps of proposed method

    图 4  某试验数据及拟合方差

    Figure 4.  Data of a test and its fitting variance

    图 5  数据分段

    Figure 5.  Data segmentation

    图 6  长度搜索过程中的方差变化

    Figure 6.  Variance change during length search

    图 7  分段拟合结果

    Figure 7.  Results of piecewise fitting

    图 8  滤波结果及对应残差

    Figure 8.  Filtered results and corresponding residuals

    图 9  测试信号

    Figure 9.  Test signal

    图 10  测试信号滤波结果及对应残差

    Figure 10.  Filtered results and corresponding residuals of test signal

    图 11  测试信号及滤波后的功率谱

    Figure 11.  Power spectrum of test signals and filtered results

    图 12  某高超标模测试结果

    Figure 12.  Test results of a hypervelocity normal mode

    图 13  某试验模型测试结果

    Figure 13.  Test results based on some test model

    表  1  试验数据分析结果

    Table  1.   Analyzed results of test data

    y powerk/% power_pk/% max_dertak/% max_derta_pk/% dertak/10-6 derta_pk/10-6
    y1 0.104 4 0.115 2 0.222 3 0.245 9 -10.07 -11.11
    y2 0.035 7 0.039 4 0.083 3 0.092 0 7.91 8.73
    34.24 34.24 37.40 37.40 -78.52 -78.52
    下载: 导出CSV

    表  2  滤波效果分析

    Table  2.   Analyzed filtering results

    α/(°) 阶梯数据U0/V 滤波前数据U1/V 滤波后数据U2/V 滤波前偏差e1/% 滤波后偏差e2/%
    -6.45 0.959 8 0.955 8 0.955 2 -0.41 -0.47
    -4.30 0.911 6 0.912 4 0.908 7 0.09 -0.32
    -3.24 0.878 7 0.880 4 0.881 1 0.19 0.28
    -2.20 0.832 8 0.829 9 0.833 8 -0.35 0.12
    -1.79 0.803 1 0.807 2 0.805 8 0.52 0.33
    -1.16 0.762 7 0.767 1 0.769 2 0.58 0.85
    -0.13 0.734 0 0.735 9 0.735 3 0.27 0.19
    0.28 0.758 8 0.756 9 0.761 3 -0.25 0.33
    0.91 0.805 4 0.809 5 0.804 7 0.52 -0.08
    1.97 0.805 2 0.812 6 0.812 1 0.93 0.86
    3.02 0.809 4 0.809 3 0.812 8 -0.01 0.41
    4.08 0.851 6 0.851 9 0.851 6 0.04 0
    6.20 0.904 2 0.902 9 0.902 8 -0.13 -0.14
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-04-16
  • 录用日期:  2020-07-10
  • 刊出日期:  2021-06-20

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