Title :
Automatic classification of wind turbine structural faults using Doppler radar: Proof of concept study
Author :
Crespo-Ballesteros, Manuel ; Antoniou, Michail
Author_Institution :
Microwave Integrated Syst. Lab. (MISL), Univ. of Birmingham, Birmingham, UK
Abstract :
This paper explores the possibility in using radar to automatically classify wind turbine faults. As a first step, a number of experiments were conducted in an anechoic chamber with a small wind turbine were different faults were artificially induced. Two basic clustering methods were used. One was based on using different statistical parameters of the corresponding time-domain signatures. The other used Principal Components Analysis (PCA) on the corresponding frequency-domain signatures. Subsequently, a K-NN algorithm was used as the classifier to investigate whether or not automatic classification is fundamentally possible and to provide an initial comparison between the two clustering methods which rely on different signal domains. The proof of concept results presented in the paper indicate that this may indeed be plausible, to encourage further development of this idea.
Keywords :
Doppler radar; anechoic chambers (electromagnetic); frequency-domain analysis; principal component analysis; time-domain analysis; wind turbines; Doppler radar; K-NN algorithm; PCA; anechoic chamber; automatic classification; frequency-domain signatures; principal components analysis; statistical parameters; time-domain signatures; wind turbine structural faults; Blades; Classification algorithms; Doppler radar; Radar cross-sections; Time-domain analysis; Wind turbines; Doppler radar; radar target classification; structural health monitoring; wind turbines;
Conference_Titel :
Radar Conference (RadarCon), 2015 IEEE
Conference_Location :
Arlington, VA
Print_ISBN :
978-1-4799-8231-8
DOI :
10.1109/RADAR.2015.7131011