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Research Papers

High-Precision Positioning of Laser Beams for Vibration Measurements

[+] Author and Article Information
Olguta Marinescu

Graduate Student
e-mail: omarine@umich.edu

Bogdan I. Epureanu

Professor
Fellow ASME
e-mail: epureanu@umich.edu
Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109

1Corresponding author.

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF VIBRATION AND ACOUSTICS. Manuscript received April 16, 2013; final manuscript received September 7, 2013; published online October 23, 2013. Assoc. Editor: Paul C.-P. Chao.

J. Vib. Acoust 136(1), 011009 (Oct 23, 2013) (11 pages) Paper No: VIB-13-1109; doi: 10.1115/1.4025444 History: Received April 16, 2013; Revised September 07, 2013

Predicting the vibratory response of structures with complex geometry can be challenging especially when their properties (geometry and material properties) are not known accurately. These structures can suffer also from high modal density, which can result in small changes in structural properties creating large changes in the resonant response. To address this issue, structural properties could be accurately identified, or the structural response could be experimentally measured. Both these approaches require collecting measurements of higher order vibration modes, which have complicated shape. Consequently, high-accuracy positioning of laser beams is necessary for vibrometers based on laser Doppler velocimetry. This paper presents a methodology to address this challenge. The architecture involves a single-point vibrometer, a motion controller, translating/rotating stages, and special application software for alignment and edge detection. A key novelty of this technology is that the beam of the vibrometer is used for both detecting the edges and for measuring the vibration. Using a motion controller, the system can automatically place/scan and measure the surface of the structure with a positioning resolution of 1 μm. Experimental results are provided to demonstrate the new technique.

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References

Figures

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Fig. 3

Schematic of the laser beam alignment system

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Fig. 4

Example of laser beam angle misalignment

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Fig. 2

Electrical connection and photo currents in the PSD adopted in the alignment procedure

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Fig. 1

Setup configuration for laser beam alignment

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Fig. 5

Example of PSD data measurements

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Fig. 6

Schematic overview of the laser beam alignment procedure

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Fig. 7

LED process stages: (a) the beginning of the scan process, (b) detected edge location, and (c) the end of the scan process

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Fig. 8

LED input measurements and parameters: (a) example of sampled signal and (b) algorithm details

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Fig. 9

Overall architecture: 1—tilt stage, 2—laser vibrometer, 3—test structure, 4—rotary table, 5—2D linear table, and 6—laser vibrometer stand

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Fig. 18

Statistical results focused on the effects of the speed of the 2D linear table on the LED algorithm. (a) Slow scanning of one edge point, (b) medium scanning of one edge point, (c) fast scanning of one edge point, (d) slow scanning of another edge point, (e) medium scanning of another edge point, and (f) fast scanning of another edge point.

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Fig. 10

Convergence plots for the Gauss–Seidel based method used for minimizing misalignment between the laser beam and the axis of the rotary table

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Fig. 11

Scanning of a test structure using the LED algorithm

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Fig. 12

Resolution of the LED algorithm

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Fig. 13

Influence of different operating speeds of the 2D linear table on the LED algorithm revealing the total measurement time required. (a) Standard deviation of the detected edge location and (b) mean value of the detected edge location.

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Fig. 14

Correction for the laser intensity signal processing delays

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Fig. 15

Noise reduction for the LED algorithm

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Fig. 16

Influence of the number of averages per scan set in the LED algorithm

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Fig. 17

Influence of the laser focus level and the diameter of the laser beam (D) on the LED algorithm

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Fig. 19

Statistical results focused on the influence of different laser focus levels on the LED algorithm. (a) High laser focus level, (b) medium laser focus level, and (c) low laser focus level.

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Fig. 20

Statistical results focused on the influence of the mask at two different scanned points on the LED algorithm. (a) Medium scanning of one edge point and (b) medium scanning of another edge point.

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