基于希尔伯特-黄变换的往复运动摩擦力信号分析
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摘要
往复运动中的摩擦力信号往往是非平稳信号,采用经验模式分解法可以自适应地分解这些非线性、非平稳信号,合理地提取其信号特征。应用希尔伯特-黄变换方法,分析不同往复速度和载荷条件下往复运动产生的摩擦力信号,并提取时频段能量比及其标准差,研究其润滑状态特征。结果表明:通过希尔伯特-黄变换并结合能量比分析,可以很好地反映出往复运动过程中润滑状态的变化;在一定载荷下,随着往复速度的增加,摩擦力频率成分趋于平稳,能量比标准差则逐渐减小;在一定往复速度下,随着载荷的增加,润滑状态变差,消耗的能量随之增大,能量比标准差逐渐减小;和往复速度相比,载荷对摩擦力频率分布影响相对较小。
Reciprocating force signal is usually non-stationary. The empirical mode decomposition( EMD) method can decompose these nonlinear and non-stationary signals adaptively,and extract the signal characteristics reasonably. The force signals of reciprocating movement under different speed and load conditions were analyzed by applying Hilbert-Huang transform( HHT) method,the energy ratio of time-frequency band and its standard deviation was extracted to study the lubrication state characteristics of reciprocating movement. The result shows that HHT combined with the energy ratio analysis is a very good way to reflect the variation of lubrication condition in the process of reciprocating movement. Under certain load condition,the friction frequency is tended to be stabilized,and the standard deviation of energy ratio is decreased with increasing of reciprocating speed. At a certain reciprocating speed condition,the lubrication state is gotten worse,and the consumption of energy is increased,but the standard deviation of energy ratios is decreased gradually along with increasing of the loads. As compared with reciprocating speed,the load has smaller effect on friction frequency distribution.
引文
[1]温诗铸,黄平.摩擦学原理[M].北京:清华大学出版社,2012.
    [2]Huang Norden E.The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis[J].Proceedings of the Royal Society,1998,A 454:903-995.
    [3]张郁山.希尔伯特-黄变换(HHT)与地震动时程的希尔伯特谱[D].北京:中国地震局地球物理研究所,2003.
    [4]黄光南.希尔伯特黄变换及其在地震资料分析处理中的应用[D].北京:中国海洋大学海洋地球科学学院,2009.
    [5]阮有兴.基于希尔伯特-黄变换的移动荷载作用下桥梁健康监测方法研究[D].长春:吉林大学交通学院,2013.
    [6]Han Janping,Zheng Peijuan,Wang Hongtao.Structural modal parameter identification and damage diagnosis based on HilbertHuang transform[J].Earthquake Engineering and Engineering Vibration,2014,13(1):101-111.
    [7]Tseng Yi-Li,Ko Pin-Yu,Jaw Fu-Shan.Detection of the third and fourth heart sounds using Hilbert-Huang transform[J].Bio Medical Engineering On Line,2012,11:8.
    [8]Li Helong,Kwong Sam,Yang Lihua,et al.Hilbert-Huang transform for analysis of heart rate variability in cardiac health[J].IEEE/ACM Transactions on Computational Biology and Bioinformatics,2011,8(6):1557-1567.
    [9]Xu Lijia.Study on fault detection of rolling element bearing based on translation-invariant denoising and Hilbert-Huang transform[J].Journal of Computers,2012,7(5):1142-1146.
    [10]夏均忠,苏涛,马宗坡,等.基于EMD的滚动轴承故障特征提取方法[J].噪声与振动控制,2013,33(2):123-127.Xia Junzhong,Su Tao,Ma Zongpo,et al.Fault feature extraction methods of ball bearings based on EMD[J].Noise and Vibration Control,2013,33(2):123-127.
    [11]贺智,王强,沈毅,等.希尔伯特-黄变换端点效应抑制算法综述[J].软件,2011,32(10):1-7.He Zhi,Wang Qiang,Shen Yi,et al.Survey on end effects mitigation of Hilbert-Huang transform[J].Software,2011,32(10):1-7.

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