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Research Article

A Novel Image-Based Long-Range Continuously Scanning Laser Doppler Vibrometer for Operational Modal Analysis of a Rotating Structure

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Published online: 18 Jul 2024
 

ABSTRACT

A novel image-based long-range tracking continuously scanning laser Doppler vibrometer (CSLDV) is developed to measure vibration of a rotating structure with a complex background. The image-based long-range tracking CSLDV can track and scan the rotating structure by processing its images captured by a camera in the image-based long-range tracking CSLDV. A novel image-processing method with a background averaging technique is developed to extract the rotating structure from the background in captured images and determine its location. A one-dimensional scan scheme is used to scan along a straight line along the rotating structure. An improved demodulation method is used to process measurements of the image-based long-range tracking CSLDV to estimate modal parameters of the rotating structure, including damped natural frequencies and undamped mode shapes. Experiments of tracking and scanning a rotating blade are conducted to validate vibration measurement of a rotating blade using the image-based long-range tracking CSLDV. Measured responses of the rotating blade are processed to estimate its speeds and modal parameters. The first three damped natural frequencies of out-of-plane vibration of the rotating blade and the first three undamped mode shapes of the rotating blade along its middle line are successfully estimated and compared with results from the finite element model of the corresponding stationary blade.

Acknowledgment

The authors would like to thank Dan Feng for some valuable discussion on the background averaging method.

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Supplemental material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/09349847.2024.2376225

Additional information

Funding

This work was funded by the 2022 American Society for Nondestructive Testing Fellowship Award and the National Science Foundation through Grant No. CMMI-1763024.

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