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2015 | OriginalPaper | Chapter

69. Using Remote Sensing Technologies for Wind Turbine/Farm Health Monitoring

Authors : Muammer Ozbek, Daniel J. Rixen

Published in: Progress in Clean Energy, Volume 2

Publisher: Springer International Publishing

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Abstract

Efficient use of contemporary measurement systems (accelerometers, piezoelectric or fiber-optic strain gauges) in structural health monitoring of wind turbines is mainly limited due to high sensor installation costs, practical limitations in placing these sensors on existing structures, low spatial resolution, and similar disadvantages caused by the complicated nature of wind loading and the turbine structure. The factors affecting the performance of these sensors such as sensitivity to lightning, electromagnetic fields, humidity and temperature variations, and the corresponding error compensation methods are still being investigated. Similarly, additional long-term durability tests are required to determine whether the bonding between the sensor and composite blade material deteriorates over time due to repetitive loading and severe environmental factors or not.
In this work, two optical measurement techniques (photogrammetry and laser interferometry), which do not require any sensors to be installed on the structure, are introduced as promising and versatile alternatives for measuring the vibration response of wind turbines. By using LDV (laser Doppler vibrometer), the dynamic behavior of the turbine at parked condition can be measured with a very high accuracy (in micron level). Similarly, photogrammetry enables the in-operation vibration response of the turbine to be measured with an average accuracy of ±25 mm from a measurement distance of 220 m. Considering the fact that during rotation peak-to-peak blade deformations can be as high as 1,000 mm, this accuracy can be considered as quite high and still be improved further.

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Metadata
Title
Using Remote Sensing Technologies for Wind Turbine/Farm Health Monitoring
Authors
Muammer Ozbek
Daniel J. Rixen
Copyright Year
2015
DOI
https://doi.org/10.1007/978-3-319-17031-2_69