Liao, Yi-Hsiang, Wang, Lijuan, Yan, Yong (2026) Flap-wise vibration frequency measurement of wind turbine blades through Moiré Pattern analysis. Measurement: Energy, 10 . E-ISSN 2950-3450. (doi:10.1016/j.meaene.2026.100107) (KAR id:115528)
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| Official URL: https://doi.org/10.1016/j.meaene.2026.100107 |
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Abstract
Accurate vibration measurement of blades is essential for monitoring wind turbines to reduce downtime and ensure operational safety in wind farms. Although imaging-based methods such as digital image correlation and photogrammetry have been applied to achieve non-contact vibration measurement of wind turbine blades, these methods require two or more cameras, complex synchronisation and calibration. This paper proposes a single camera-based approach to measure the vibration frequency in flap-wise direction (i.e. the direction perpendicular to the rotor disk plane) by analysing the moiré pattern generated by a marker on a blade. Experiments were conducted on a laboratory test rig to assess the proposed measurement method for different camera distances, spatial periods of marker pattern, camera pitch and yaw angles, and vibration frequencies. The results show that the moiré pattern analysis method is able to accurately determine the vibration frequency up to 30 Hz with a camera frame rate of 60 fps, compared with the reference vibration frequency obtained from a commercial accelerometer. The developed method provides a feasible and robust way for measuring flap-wise vibration frequency of wind turbine blades under laboratory conditions.
| Item Type: | Article |
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| DOI/Identification number: | 10.1016/j.meaene.2026.100107 |
| Uncontrolled keywords: | wind turbine blades; flap-wise vibration measurement; Moiré pattern analysis; image processing |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) > TA165 Engineering instruments, meters etc. Industrial instrumentation |
| Institutional Unit: | Schools > School of Engineering, Mathematics and Physics > Engineering |
| Former Institutional Unit: |
There are no former institutional units.
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| Funders: | University of Kent (https://ror.org/00xkeyj56) |
| Depositing User: | Lijuan Wang |
| Date Deposited: | 01 Jun 2026 16:23 UTC |
| Last Modified: | 22 Jul 2026 10:19 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/115528 (The current URI for this page, for reference purposes) |
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https://orcid.org/0000-0002-2517-2728
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