RT info:eu-repo/semantics/article
T1 Fault detection of wind turbine induction generators through current signals and various signal processing techniques
A1 Merizalde Zamora, Yury Humberto
A1 Hernández Callejo, Luis
A1 Duque Pérez, Óscar
A1 López Meraz, Raúl Alberto
K1 Ingeniería
K1 Tecnología
K1 Wind turbine
K1 Electric generator
K1 Fault diagnosis
K1 Turbina eólica
K1 Generador eléctrico
K1 Diagnóstico erróneo
K1 3306 Ingeniería y Tecnología Eléctricas
AB In the wind industry (WI), a robust and effective maintenance system is essential. To minimize the maintenance cost, a large number of methodologies and mathematical models for predictive maintenance have been developed. Fault detection and diagnosis are carried out by processing and analyzing various types of signals, with the vibration signal predominating. In addition, most of the published proposals for wind turbine (WT) fault detection and diagnosis have used simulations and test benches. Based on previous work, this research report focuses on fault diagnosis, in this case using the electrical signal from an operating WT electric generator and applying various signal analysis and processing techniques to compare the effectiveness of each. The WT used for this research is 20 years old and works with a squirrel-cage induction generator (SCIG) which, according to the wind farm control systems, was fault-free. As a result, it has been possible to verify the feasibility of using the current signal to detect and diagnose faults through spectral analysis (SA) using a fast Fourier transform (FFT), periodogram, spectrogram, and scalogram.
PB MDPI
YR 2020
FD 2020
LK https://uvadoc.uva.es/handle/10324/58735
UL https://uvadoc.uva.es/handle/10324/58735
LA eng
NO Appl. Sci. 2020, vol.10, n. 21, 7389
NO Producción Científica
DS UVaDOC
RD 30-may-2024