The Use of Coherence Functions of Acoustic Emission Signals as a Method for Diagnosing Wind Turbine Blades

Abstract

Acoustic emission (AE) is one of the methods of non-destructive evaluation (NDE), and functions by means of detecting elastic waves caused by dynamic movements in AE sources, such as cracking in various material structures. In the case of offshore wind turbines, the most vulnerable components are their blades. Therefore, the authors proposed a method using AE to diagnose wind turbine blades. In the identification of their condition during monitoring, it was noted that the changes characterising blade damage involve non-linear phenomena; hence, wave phenomena do not occur in the principal components of the amplitudes or their harmonics. When the authors used the inverse transformation in the signal analysis process, which essentially leads to finding a signal measure, it allowed them to distinguish the wave spectrum of an undamaged system from one in which the material structure of the blade was damaged. The characteristic frequencies of individual phenomena interacting with the blade of a working turbine provide the basis for the introduction of filters (or narrowband sensors) that will increase the quality of the diagnosis itself. Considering the above, the use of the coherence function was proposed as an important measure of a diagnostic signal, reflecting a given condition of the blade.