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Jesus A. Carino
Also published under:Jesús A. Carino, J. Cariño, J. A. Carino, J. A. Cariño
Affiliation
MCIA Research Center, Technical University of Catalonia (UPC), Terrassa, Spain
Topic
Operating Conditions,Industrial Plants,Neural Network,Self-organizing Map,Auxiliary Signal,Dimensionality Reduction,Fault Scenarios,Input Space,Manufacturing Process,Model Input,Novelty Detection,Output Space,Performance Metrics,State Machine,Support Vector Machine,Target Signal,Training Set,Weight Vector,Coefficient Of Performance,Compressor,Critical Signaling,Data-driven Methodology,Dimensionality Reduction Approach,Electric Power,Electromechanical System,Empirical Mode Decomposition,Fault Diagnosis,Fault Identification,Feature Reduction,Friction Test,Generalization Capability,Identification Methodology,Industrial Data,Learning Rate,Linear Discriminant Analysis,Matching Unit,Mean Absolute Error,Mean Absolute Percentage Error,Output Grid,Potential Savings,Real Plant,Refrigerator,Suction Pressure,Torque Signal,Wet Bulb,Abnormal Situations,Accuracy And Precision,Adaptive Neuro-fuzzy Inference System,Aggregate Signal,Anomaly Detection,
Biography
Jesus A. Carino (M’13) received the M.S. degree in electrical engineering from the University of Guanajuato, Mexico, in 2012, and the Ph.D. degree in electronics engineering from the Technical University of Catalonia (UPC), Barcelona, Spain. His research interests include fault diagnosis in electric machines, novelty detection, pattern recognition, artificial intelligence applied to industrial processes monitoring, data analytics, and digital signal processing on FPGAs for applications in mechatronics.