Palavra-chave: CONDITION MONITORING

ETL INSTRUMENTED RAILWAY VEHICLE HYDRODYNAMIC BEARING WEAR HYDRODYNAMIC BEARINGS WEAR STABILITY ROTORDYNAMICS TIME RESPONSE DYNAMIC ANALYSIS SIMULATION-DRIVEN DEEP LEARNING DEEP LEARNING HYDRODYNAMIC JOURNAL BEARINGS FAULT CLASSIFICATION AUTOENCODERS FAULT DETECTION CONVOLUTIONAL NEURAL NETWORK MACHINE LEARNING OVALIZATION FAULT ARTIFICIAL INTELLIGENCE STATISTICAL INDICATORS FOUNDATION STRUCTURE AUTOMATIC OMA FAULT IDENTIFICATION AND ISOLATION WEAR FAULT STRUCTURAL HEALTH MONITORING DATA SCIENCE HYDRODYNAMIC JOURNAL BEARING