Design and control of a mechatronic system for the homogenization of compost in anaerobic digesters. - Gustavo Aguilar Alvarez; Luis Alberto Morales-Hernández; Luis Morales-Velazquez; Juan Jose Saucedo Dorantes (CONIELECOMP, 2013)

Reliable methodology for gearbox wear monitoring based on vibration analysis. - Juan Jose Saucedo Dorantes; Armando Guadalupe Garcia-Ramirez; Juan Carlos Jáuregui-Correa; Roque Alfredo Osornio-Rios; Arturo Garcia-Perez; René de Jesús Romero-Troncoso (IECON, 2014)

Novelty Detection based Condition Monitoring Scheme Applied to Electromechanical Systems. - Miguel Delgado Prieto; Jesus A. Carino; Juan Jose Saucedo Dorantes; Roque Alfredo Osornio-Rios; Luis Romeral; René de Jesús Romero-Troncoso (ETFA, 2018)

Incremental Learning Framework-based Condition Monitoring for Novelty Fault Identification Applied to Electromechanical Systems. - Juan Jose Saucedo Dorantes; Miguel Delgado Prieto; Jesus Adolfo Carino-Corrales; Roque Alfredo Osornio-Rios; Luis Romeral Martinez; René de Jesús Romero-Troncoso (ETFA, 2018)

Statistical data fusion as diagnosis scheme applied to a kinematic chain. - Francisco Arellano-Espitia; Juan Jose Saucedo Dorantes; Roque Alfredo Osornio-Rios; Miguel Delgado Prieto; Jesus Adolfo Carino-Corrales; René de Jesús Romero-Troncoso (ICIT, 2018)

Thermography-Based Methodology for Multifault Diagnosis on Kinematic Chain. - Miguel Delgado Prieto; Jesus Adolfo Carino-Corrales; Juan Jose Saucedo Dorantes; René de Jesús Romero-Troncoso; Roque Alfredo Osornio-Rios (IEEE Trans. Ind. Informatics, 2018)

Autoencoder based feature reduction analysis applied to electromechanical systems condition monitoring. - Francisco Arellano-Espitia; Juan Jose Saucedo Dorantes; Miguel Delgado Prieto; Roque Alfredo Osornio-Rios (ETFA, 2019)

Condition monitoring approach based on dimensionality reduction techniques for detecting power quality disturbances in cogeneration systems. - Artvin Darien Gonzalez-Abreu; Juan Jose Saucedo Dorantes; Roque Alfredo Osornio-Rios; René de Jesús Romero-Troncoso; Miguel Delgado Prieto; Daniel Morinigo-Sotelo (ETFA, 2019)

Multiple-fault detection and identification scheme based on hierarchical self-organizing maps applied to an electric machine. - Juan Jose Saucedo Dorantes; Miguel Delgado Prieto; René de Jesús Romero-Troncoso; Roque Alfredo Osornio-Rios (Appl. Soft Comput., 2019)

Analysis of Machine Learning based Condition Monitoring Schemes Applied to Complex Electromechanical Systems. - Francisco Arellano-Espitia; Artvin Darien Gonzalez-Abreu; Miguel Delgado Prieto; Juan José Saucedo-Dorantes; Roque Alfredo Osornio-Rios (ETFA, 2020)

Deep Learning based Condition Monitoring approach applied to Power Quality. - Artvin Darien Gonzalez-Abreu; Juan José Saucedo-Dorantes; Roque Alfredo Osornio-Rios; Francisco Arellano-Espitia; Miguel Delgado Prieto (ETFA, 2020)

Deep-Learning-Based Methodology for Fault Diagnosis in Electromechanical Systems. - Francisco Arellano-Espitia; Miguel Delgado Prieto; Víctor Martínez-Viol; Juan Jose Saucedo Dorantes; Roque Alfredo Osornio-Rios (Sensors, 2020)

Industrial Data-Driven Monitoring Based on Incremental Learning Applied to the Detection of Novel Faults. - Juan Jose Saucedo Dorantes; Miguel Delgado Prieto; Roque Alfredo Osornio-Rios; René de Jesús Romero-Troncoso (IEEE Trans. Ind. Informatics, 2020)

Virtual reality-based tool applied in the teaching and training of condition-based maintenance in induction motors. - David Checa; Andrés Bustillo; Juan Jose Saucedo Dorantes; Roque Alfredo Osornio-Rios; Irving Armando Cruz-Albarrán (IECON, 2021)

Deep-Compact-Clustering Based Anomaly Detection Applied to Electromechanical Industrial Systems. - Francisco Arellano-Espitia; Miguel Delgado Prieto; Artvin Darien Gonzalez-Abreu; Juan Jose Saucedo Dorantes; Roque Alfredo Osornio-Rios (Sensors, 2021)

Diagnosis Methodology Based on Deep Feature Learning for Fault Identification in Metallic, Hybrid and Ceramic Bearings. - Juan Jose Saucedo Dorantes; Francisco Arellano-Espitia; Miguel Delgado Prieto; Roque Alfredo Osornio-Rios (Sensors, 2021)

Diagnosis Electromechanical System by Means CNN and SAE: An Interpretable-Learning Study. - Francisco Arellano-Espitia; Miguel Delgado Prieto; Víctor Martínez-Viol; Juan Jose Saucedo Dorantes; Roque Alfredo Osornio-Rios (ICPS, 2022)

Deep Learning-Based Partial Transfer Fault Diagnosis Methodology for Electromechanical Systems. - Francisco Arellano-Espitia; Miguel Delgado Prieto; Joan Valls-Perez; Juan Jose Saucedo Dorantes; Roque Alfredo Osornio-Rios (ETFA, 2023)

Thermography-Based Method for the Fault Diagnosis of Magnetite-Contaminated Rolling Bearings. - Roque Alfredo Osornio-Rios; Jonathan Cureño Osornio; Alvaro Ivan Alvarado-Hernandez; Israel Zamudio-Ramírez; Juan José Saucedo-Dorantes; Jose A. Antonino-Daviu (IECON, 2023)

An Entropy-Based Condition Monitoring Strategy for the Detection and Classification of Wear Levels in Gearboxes. - David Alejandro Elvira-Ortiz; Juan Jose Saucedo Dorantes; Roque Alfredo Osornio-Rios; René de Jesús Romero-Troncoso (Entropy, 2023)

State of Charge Estimation Model Based on Genetic Algorithms and Multivariate Linear Regression with Applications in Electric Vehicles. - Carlos Gustavo Manriquez-Padilla; Isaias Cueva-Perez; Aurelio Dominguez-Gonzalez; David Alejandro Elvira-Ortiz; Angel Perez-Cruz; Juan José Saucedo-Dorantes (Sensors, 2023)

SDKU-Net: A Novel Architecture with Dynamic Kernels and Optimizer Switching for Enhanced Shadow Detection in Remote Sensing. - Gilberto Alvarado-Robles; Isac Andres Espinosa-Vizcaino; Carlos Gustavo Manriquez-Padilla; Juan Jose Saucedo Dorantes (Comput., 2025)