Lifting approach to simplify output-only continuous-scan laser vibrometry

被引:27
|
作者
Yang, Shifei [1 ]
Allen, Matthew S. [1 ]
机构
[1] Univ Wisconsin, Dept Engn Phys, Madison, WI 53706 USA
基金
美国国家科学基金会;
关键词
Modal identification; Output-only modal analysis; Lifting approach; Laser Doppler vibrometry; Linear time periodic; DOPPLER VIBROMETRY; VIBRATION;
D O I
10.1016/j.ymssp.2013.11.010
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Continuous-scan laser Doppler vibrometry (CSLDV) can greatly accelerate modal testing by continuously sweeping the measuring Iaser over a structure, effectively capturing its response at tens or even hundreds of points along the laser path. Several techniques have been devised to process CSLDV measurements from structures under controlled input. The authors recently extended CSLDV to the case where the input forces are unmeasured random white noise, using the harmonic power spectrum of a time periodic system. The harmonic power spectrum is analogous to the power spectrum used in the identification of time invariant systems, but with many additional harmonics for each mode, requiring an additional effort in modal parameter estimation. This paper presents a variant on the harmonic power spectrum, proposing a simplified algorithm based on the lifting approach. Lifting causes all sideband peaks in the harmonic power spectrum to collapse into a single peak in the range from zero to half of the scan frequency, so the spectra are far easier to interpret. The proposed algorithm is first evaluated on a simulated beam, and found to give results that are comparable with those obtained by the harmonic power spectrum method, yet the data reduction with the lifting approach is much simpler. This algorithm is then employed to identify the first several modes of a parked wind turbine under wind excitation, using a new long range remote sensing vibrometer. The speckle noise is found to be remarkably small even at a standoff distance of 77 m and a surface scan velocity of 500 m/s without any surface treatment. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:267 / 282
页数:16
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