René-Vinicio Sánchez
Orcid: 0000-0003-0395-9228
According to our database1,
René-Vinicio Sánchez
authored at least 40 papers
between 2015 and 2024.
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Bibliography
2024
Scale-Fractal Detrended Fluctuation Analysis for Fault Diagnosis of a Centrifugal Pump and a Reciprocating Compressor.
Sensors, January, 2024
2023
Rainfall Forecasting using a Bayesian framework and Long Short-Term Memory Multi-model Estimation based on an hourly meteorological monitoring network. Case of study: Andean Ecuadorian Tropical City.
Earth Sci. Informatics, June, 2023
Poincaré Plot Features and Statistical Features From Current and Vibration Signals for Fault Severity Classification of Helical Gear Tooth Breaks.
J. Comput. Inf. Sci. Eng., 2023
2022
Gear and bearing fault classification under different load and speed by using Poincaré plot features and SVM.
J. Intell. Manuf., 2022
A hybrid prototype selection-based deep learning approach for anomaly detection in industrial machines.
Expert Syst. Appl., 2022
Deep Ensemble-Based Classifier for Transfer Learning in Rotating Machinery Fault Diagnosis.
IEEE Access, 2022
2021
One-Shot Fault Diagnosis of Three-Dimensional Printers Through Improved Feature Space Learning.
IEEE Trans. Ind. Electron., 2021
2020
Fault Diagnosis of Wind Turbine Gearbox Based on the Optimized LSTM Neural Network with Cosine Loss.
Sensors, 2020
J. Frankl. Inst., 2020
Knowledge extraction from deep convolutional neural networks applied to cyclo-stationary time-series classification.
Inf. Sci., 2020
Bayesian approach and time series dimensionality reduction to LSTM-based model-building for fault diagnosis of a reciprocating compressor.
Neurocomputing, 2020
2019
IEEE Trans. Fuzzy Syst., 2019
A hybrid heuristic algorithm for evolving models in simultaneous scenarios of classification and clustering.
Knowl. Inf. Syst., 2019
Finite-time leaderless consensus control of a group of Euler-Lagrangian systems with backlash nonlinearities.
J. Frankl. Inst., 2019
Using a Support Vector Machine Based Decision Stage to Improve the Fault Diagnosis on Gearboxes.
Comput. Intell. Neurosci., 2019
Spur Gear Fault Diagnosis Using a Multilayer Gated Recurrent Unit Approach With Vibration Signal.
IEEE Access, 2019
Generative Adversarial Networks Selection Approach for Extremely Imbalanced Fault Diagnosis of Reciprocating Machinery.
IEEE Access, 2019
2018
Feature ranking for multi-fault diagnosis of rotating machinery by using random forest and KNN.
J. Intell. Fuzzy Syst., 2018
Feature engineering based on ANOVA, cluster validity assessment and KNN for fault diagnosis in bearings.
J. Intell. Fuzzy Syst., 2018
Gearbox fault classification using dictionary sparse based representations of vibration signals.
J. Intell. Fuzzy Syst., 2018
J. Intell. Fuzzy Syst., 2018
A semi-supervised approach based on evolving clusters for discovering unknown abnormal condition patterns in gearboxes.
J. Intell. Fuzzy Syst., 2018
Echo state network and variational autoencoder for efficient one-class learning on dynamical systems.
J. Intell. Fuzzy Syst., 2018
An adaptive genomic difference based genetic algorithm and its application to memetic continuous optimization.
Intell. Data Anal., 2018
A fuzzy transition based approach for fault severity prediction in helical gearboxes.
Fuzzy Sets Syst., 2018
IEEE Access, 2018
2017
Microelectron. Reliab., 2017
A Bayesian approach to consequent parameter estimation in probabilistic fuzzy systems and its application to bearing fault classification.
Knowl. Based Syst., 2017
Attribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery.
Expert Syst. Appl., 2017
Automatic feature extraction of time-series applied to fault severity assessment of helical gearbox in stationary and non-stationary speed operation.
Appl. Soft Comput., 2017
SOA Based Integrated Software to Develop Fault Diagnosis Models Using Machine Learning in Rotating Machinery.
Proceedings of the 2017 IEEE Symposium on Service-Oriented System Engineering, 2017
2016
Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning.
Sensors, 2016
J. Intell. Fuzzy Syst., 2016
A statistical comparison of neuroclassifiers and feature selection methods for gearbox fault diagnosis under realistic conditions.
Neurocomputing, 2016
Observer-biased bearing condition monitoring: From fault detection to multi-fault classification.
Eng. Appl. Artif. Intell., 2016
Hierarchical feature selection based on relative dependency for gear fault diagnosis.
Appl. Intell., 2016
A methodological framework using statistical tests for comparing machine learning based models applied to fault diagnosis in rotating machinery.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2016
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016
2015
Multi-Stage Feature Selection by Using Genetic Algorithms for Fault Diagnosis in Gearboxes Based on Vibration Signal.
Sensors, 2015
Multimodal deep support vector classification with homologous features and its application to gearbox fault diagnosis.
Neurocomputing, 2015