Wavelet and Hilbert Huang Transforms Applied to Park’s Vector for Fault Detection in a PMSG Wind Turbine
Raúl Arturo Ortiz-Medina, Mauricio Sanabria-Villamizar, Irvin López-García, Francisco Javier Villalobos-Piña, Francisco Beltrán-Carbajal, Víctor Arturo Maldonado-Ruelas
Abstract
This article is a novel technique for the maintenance of machines, specifically in wind turbines. The technique proposes a fault detection method, identifying the pattern frequencies of the disturbance mode. This methodology is carried out with the Discrete Fourier Transform, Wavelet Transform and the Hilbert-Huang Transform, making the comparison in the described case. On the other hand, the methodology shows us the frequencies detected by each technique and the differences between them.
Topics & Concepts
Wavelet transformHilbert–Huang transformWind powerFault (geology)TurbineHilbert transformDiscrete wavelet transformWaveletMode (computer interface)Fault detection and isolationFourier transformComputer scienceContinuous wavelet transformAlgorithmS transformControl theory (sociology)Pattern recognition (psychology)MathematicsArtificial intelligenceEngineeringComputer visionMathematical analysisGeologyTelecommunicationsSpectral densitySeismologyAerospace engineeringElectrical engineeringControl (management)Operating systemActuatorFilter (signal processing)Machine Fault Diagnosis TechniquesFault Detection and Control SystemsStructural Health Monitoring Techniques