Localized damage detection in wind turbine rotor blades using airborne acoustic emissions

authored by: Alexander Lange, Reemt Hinrichs, Jörn Ostermann
Abstract: The human-induced climate change is one of the biggest threats for modern society. Wind energy turbines play a key role in the necessary transformation of the energy sector and their reliable, low-maintenance operation with short downtimes is therefore of particular interest. To this end, automated structural health monitoring (SHM) gained a lot of interest in research and economy. In this work, we propose an algorithm for damage detection in rotor blades using airborne acoustic emissions (AE). Our algorithm inherently uses a localization approach and is therefore not only able to detect a structural damage but also to estimate its position using time differences of arrival (TDoA) of airborne sound waves. Since we intend only an approximate localization of the impulsive damage sounds, we suggest a simple yet effective method based on cross-correlation of energy-envelope functions to estimate the TDoA. For the task of damage detection and localization, only two line-of-sight microphones are required, which makes this approach very economic for SHM. We evaluate our method on two large-scale fatigue tests conducted on a 34-meter and a 30-meter rotor blade under laboratory conditions. During the fatigue tests, we continuously recorded airborne sound signals with multiple microphones placed inside the rotor blades. With our proposed method, we are able to detect and correctly assign the two significant structural damages in both rotor blades to a two-meter-long rotor blade zone without having any false-positive alarms throughout more than 350 hours of continuous audio recordings. Airborne acoustic emissions therefore may be a promising alternative to other conventional monitoring solutions based on structure-borne sound, which usually require considerable denser sensor networks.
Organisation(s): Institute of Information Processing
L3S Research Centre
Type: Conference contribution
Pages: 228-235
No. of pages: 8
Publication date: 30.03.2023
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: General Materials Science
Sustainable Development Goals: SDG 3 - Good Health and Well-being, SDG 13 - Climate Action
Electronic version(s): https://doi.org/10.21741/9781644902455-29 (Access: Open)