A nearly end-to-end deep learning approach to fault diagnosis of wind turbine gearboxes under nonstationary conditions
Liangwei Zhang, Qi Fan, Jing Lin, Zhicong Zhang, Xiaohui Yan, Chuan Li
Topics & Concepts
Computer scienceHilbert–Huang transformFault (geology)Deep learningConvolutional neural networkTurbineArtificial intelligenceWind powerEnd-to-end principleReliability (semiconductor)PreprocessorPattern recognition (psychology)Machine learningPower (physics)Computer visionEngineeringQuantum mechanicsMechanical engineeringGeologyElectrical engineeringSeismologyFilter (signal processing)PhysicsMachine Fault Diagnosis TechniquesGear and Bearing Dynamics AnalysisMechanical Failure Analysis and Simulation