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Intelligent Diagnosis and Forecast of the Condition of Rotating Machinery in the Context of Industry 40
Sanchez Loja, Rene Vinicio
(PI)
Cajas Muñoz, Franco David
(CoI)
Li, Chuan
(CoI)
Lucero Otorongo, Pablo Moises
(CoI)
Macancela Poveda, Jean Carlo
(CoI)
Pacheco Cordova, Edison Eugenio
(CoI)
Siguencia Urgiles, Julio Fernando
(CoI)
Torres Diaz, Cristian Paul
(CoI)
de Oliveira, José Valente
(CoI)
Vásquez, Rafael
(CoI)
Calle Lazo, Ana Karla
(Student)
Llivicura Orellana, Holger Florencio
(Student)
Montalvo Ureta, Douglas Vladimir
(Student)
Ortega Lucero, Luis Renato
(Student)
Ortiz Farfan, Christian German
(Student)
Vacacela Costa, Andres Segundo
(Student)
Zambrano Mendoza, Jonathan Xavier
(Student)
Cabrera Mendieta, Diego Roman
(Col)
Cerrada Lozada, Mariela
(Col)
Guaman Buestan, Adriana Del Pilar
(Col)
Llerena Pizarro, Omar Rosendo
(Col)
Villacis Marin, Mauricio Leonardo
(Col)
Group for Research and Development in Industrial Technologies (GIDTEC)
Universidade do Algarve (Ualg)
Universidad Pontificia Bolivariana (UPB)
Overview
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Project Details
Description
General objective Determine the sensitivity of the estimated load torque signal
Status
Active
Effective start/end date
23/01/20
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Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
Rotating machinery
Engineering & Materials Science
100%
Torque
Engineering & Materials Science
60%
Industry
Engineering & Materials Science
35%