采样长度对阻尼识别的影响

Abstract
Figure/Table
References (16)
Related Citation (15)

Download: PDF (896 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

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

Received: 10 January 2018 Published: 15 May 2019

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	YAN Kai1
	ZHAO Xiaodan1
	LIAN Haiping1
	CHENG Hui1
	SUN Liming2

Cite this article:

YAN Kai1,ZHAO Xiaodan1,LIAN Haiping1, et al. Influence of sampling length on the damping identification[J]. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(10): 119-123.

URL:

http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/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.