采样长度对阻尼识别的影响

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摘要传统观点认为阻尼识别方法受截断误差影响；增加采样长度，即增加采样点数，提高频率分辨率，可以减少误差，形成了采样时间长（即采样点数多）阻尼识别误差小的观点。但实际采样信号中包含噪声，对采样信号进行傅里叶变换时，噪声信号随阻尼信号一同被积分。将振动衰减信号作傅里叶变换，得出当采样时间超过4.6/n（n为阻尼值）时振动衰减信号频谱幅值与采样点数呈反比关系；对噪声使用统计分析，噪声频谱实际发生值不是期望值，而是主要在期望值与三倍标准差之间浮动，将噪声信号作积分推导得出噪声频谱幅值与采样点数的开方值呈反比关系。得出采样时间过长时，噪声信号将掩盖振动衰减信号，导致阻尼识别误差变大，通过计算推导得出了采样点数临界值的计算公式。运用仿真算例与悬臂梁敲击实验进行了验证。

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	闫凯1
	赵晓丹1
	连海平1
	程惠1
	孙黎明2

关键词 ：采样点数, 傅里叶变换, 噪声, 频谱, 阻尼

Abstract：Conventional view holds that the damping identification method is influenced by truncation error, increasing the number of sampling points and improving the frequency resolution can reduce errors,forming a view that the more the sampling points, the smaller the damping identification error.But, the actual sampling signal usually contains noise, when the Fourier transform is applied on the sampling signal, the noise signal is also integrated together with the damping signal.It is found doing the Fourier transform on a vibration attenuation signal with the sampling time over 4.6/n(n is damping value), the amplitude of the vibration attenuation signal is inversely proportional to the number of sampling points.When using the statistical analysis on a noise signal, the actual occurrence value of the noise spectrum is not the expected value but mainly fluctuates between the expected value and the tripple of standard deviation.Through the inner product operation of the noise signal, it is shown the noise spectrum amplitude is inversely proportional to the square root of the sampling points.When the sampling time is too long, the noise signal will cover the vibration attenuation signal, which results in a larger damping identification error.Through calculations, the formula of sampling threshold was derived and verified by simulation examples and cantilever beam experiments.

Key words： sampling points Fourier transform noise frequency spectrum damping ratio

收稿日期: 2018-01-10 出版日期: 2019-05-15

引用本文:

闫凯1,赵晓丹1,连海平1,程惠1,孙黎明2. 采样长度对阻尼识别的影响[J]. 振动与冲击, 2019, 38(10): 119-123.
YAN Kai1，ZHAO Xiaodan1，LIAN Haiping1，CHENG Hui1，SUN Liming2. Influence of sampling length on the damping identification. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(10): 119-123.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2019/V38/I10/119

[1] 应怀樵，沈松，刘进明. “ZOOMBDFT”法高精度求系统阻尼比的探讨[J]. 振动.测试与诊断，1997，(2)：44-48.
YING Huai-qiao, SHEN Song, LIU Jin-ming. Investigation on high precision calculation for damping ratio using “ZOOMBDFT” method [J]. Journal of Vibration. Measurement & Diagnosis, 1997, (2): 44-48.
[2] 裴强，王丽. 结构参数识别方法研究[J]. 大连大学学报，2013，34(6)：36-44.
PEI Qiang, WANG Li. Review of parameter identification methods for vibrating system [J]. Journal of Dalian University, 2013, 34(6):36-44.
[3] 应怀樵，李惠彬，沈松. 关于用INV的频率细化与大容量数据采集分析技术提高阻尼比的计算精度的研究[J]. 噪声与振动控制，1997，(2)：17-20.
YING Huai-qiao, LI Hui-bin, SHEN Song. The research of improving damping ratios calculation accuracy hased on INV of zoom broad data fourier transform [J]. Journal of Noise and Vibration Control, 1997, (2):17-20.
[4] 陈奎孚，焦群英. 半功率点法估计阻尼比的误差分析[J]. 机械强度，2002，(4)：510-514.
CHEN Kui-fu, JIAO Qun-ying. Influence of linear interpolation approximation to half power points on the damping estimation precision [J]. Journal of Mechanical Strength, 2002(4): 510-514.
[5] 陈奎孚，张森文. 半功率法估计阻尼的一种改进[J]. 振动工程学报，2002，15(2)：151-155.
CHEN Kui-fun, ZHANG Sen-wen. Improvement on the damping estimation by half power point method [J]. Journal of Vibration Engineering, 2002, 15(2): 151-155.
[6] 胡峰，吴波，胡友民，等. 利用粒子群优化算法实现阻尼比和频率的精确识别[J]. 振动与冲击，2009，28(7)：8-11.
HU Feng, WU Bo, HU You-min, et al. Accurate identification of damping ratio and frequency by particle swarm optimization [J]. Journal of Vibration and Shock, 2009, 28(7): 8-11.
[7] 苏向荣，丁康，谢明. 用传递函数估计小阻尼的新方法[J]. 机械科学技术，2003，22(5)：717-720.
SU Xiang-rong, DING Kang, XIE Ming. A new method for exactly estimating small damping by transfer function [J]. Mechanical Science and Signal Processing, 2003, 22(5): 717-720.
[8] 丁康，谢明，苏向荣.一种精确计算结构小阻尼的新方法[J].西安交通大学学报，2003,(9):929-932.
DING Kang, XIE Ming, SU Xiang-rong.New method for exact estimation of small damping of structure [J]. Journal of Xi’an Jiaotong University, 2003, (9): 929-932.
[9] 赵晓丹，徐俊杰，王西富. 利用分段积分识别阻尼比研究[J].振动与冲击，2015，34(20)：109-114.
ZHAO Xiao-dan, XU Jun-jie, WANG Xi-fu. Using piecewise integral identification damping ratio study [J]. Journal of Vibration and Shock, 2015, 34 (20): 109-114.
[10] 陈正林. 内积模极值方法在曲轴阻尼识别中的运用[J]. 内燃机，2015(4)：39-41.
CHEN Zheng-lin. Application of inner product modulus maximum method in damping identification of crankshaft [J]. Internal Combustion Engines, 2015(4): 39-41.
[11] 刘汉夫. 桥梁阻尼测试与分析方法研究[J]. 铁道建筑，2011，(2)：7-10.
LIU Han-fu. Bridge damping test and analysis methods [J]. Railway Engineering, 2011(2): 7-10.
[12] 苏向荣. 随机噪声对频谱校正精度的影响和结构小阻尼的精确估计[D]. 汕头：汕头大学，2004.
SU Xiang-rong. Random noise influence on spectrum correcting methods and exactly estimate small damping of a structure [D]. Shantou: Shantou University, 2004.
[13] 赵红发，南广仁. Riemann-Lebesgue定理的推广[J]. 长春师范学院学报：人文社会科学版，2008，7(5)：3-4.
ZHAO Hong-fa, NAN Guang-ren. The extension of Riemann-Lebesgue theorem [J]. Journal of Changchun Normal University(Humanities and Social Sciences), 2008, 7(5): 3-4.
[14] 赵晓丹,刘涛. 基于内积模极值的小阻尼计算新方法[J]. 机械科学与技术，2009，28(10)：1308-1310.
ZHAO Xiao-dan, LIU Tao. A new method of small damping calculation based on the extreme value of inner product model [J]. Mechanical Science and Technology, 2009, 28(10): 1308-1310.
[15] 陆旋. 数理统计基础[M]. 北京：清华大学出社，2004.
LU Xuan. Mathematical statistics basis [M]. Beijing: Tsinghua University, 2004.
[16] 西蒙赫金.信号与系统[M].北京:电子工业出版社.2006
SimonHaykin. Signals and Systems [M]. Beijing: Publishing House Of Electronics Industry, 2006.