Year: 2016
Type: conference-paper
Abstract: This study presents a system that is able to detect defects like cracks, leading/trailing edge opening or delamination of at least 15 cm size, remotely, without stopping the wind turbine.The system is vibration-based: mechanical energy is artificially introduced by means of an electromechanical actuator, whose plunger periodically hits the blade.The induced vibrations propagate along the blade and are picked up by an array of accelerometers.The vibrations in mid-range frequencies are utilized: this range is above the frequencies excited by blade-wind interaction, ensuring a good signal-to-noise ratio.At the same time, the corresponding wavelength is short enough to deliver required damage detection resolution and long enough to be able to propagate the entire blade length.The paper demonstrates the system on a 225 kW Vestas V27 wind turbine.One blade of the wind turbine was equipped with the system and a 3.5 month monitoring campaign was conducted while the turbine was operating normally.During the campaign, a defect -a trailing edge opening -was artificially introduced into the blade and its size was gradually increased from the original 15 cm to 45 cm.Using an unsupervised learning algorithm, we were able to detect even the smallest amount of damage while the wind turbine was operating under different weather conditions.The paper provides the detailed information about the instrumentation and the measurement campaign and explains the damage detection algorithm.
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2610885738