Bearing Fault Diagnosis Based on Convolutional Neural Networks with Kurtogram Representation of Acoustic Emission Signals. - Alexander E. Prosvirin; Jaeyoung Kim; Jong-Myon Kim (CSA/CUTE, 2017)

Towards bearing health prognosis using generative adversarial networks: Modeling bearing degradation. - Sheraz Ali Khan; Alexander E. Prosvirin; Jong-Myon Kim (ICACS, 2018)

Intelligent Rub-Impact Fault Diagnosis Based on Genetic Algorithm-Based IMF Selection in Ensemble Empirical Mode Decomposition and Diverse Features Models. - M. M. Manjurul Islam; Alexander E. Prosvirin; Jong-Myon Kim (IDEAL (1), 2018)

Rub-Impact Fault Diagnosis Using an Effective IMF Selection Technique in Ensemble Empirical Mode Decomposition and Hybrid Feature Models. - Alexander E. Prosvirin; M. M. Manjurul Islam; Jaeyoung Kim; Jong-Myon Kim (Sensors, 2018)

Reliable fault diagnosis of bearings with varying rotational speeds using envelope spectrum and convolution neural networks. - Dileep Kumar Appana; Alexander E. Prosvirin; Jong-Myon Kim (Soft Comput., 2018)

An Improved Algorithm for Selecting IMF Components in Ensemble Empirical Mode Decomposition for Domain of Rub-Impact Fault Diagnosis. - Alexander E. Prosvirin; M. M. Manjurul Islam; Jong-Myon Kim (IEEE Access, 2019)

Fault Identification of Multi-level Gear Defects Using Adaptive Noise Control and a Genetic Algorithm. - Cong Dai Nguyen; Alexander E. Prosvirin; Jong-Myon Kim (IHCI (1), 2020)

Multistage Centrifugal Pump Fault Diagnosis by Selecting Fault Characteristic Modes of Vibration and Using Pearson Linear Discriminant Analysis. - Zahoor Ahmad; Alexander E. Prosvirin; Jaeyoung Kim; Jong-Myon Kim (IEEE Access, 2020)

Robot manipulator active fault-tolerant control using a machine learning-based automated robust hybrid observer. - Farzin Piltan; Alexander E. Prosvirin; Jong-Myon Kim (J. Intell. Fuzzy Syst., 2020)

A Reliable Fault Diagnosis Method for a Gearbox System with Varying Rotational Speeds. - Cong Dai Nguyen; Alexander E. Prosvirin; Jong-Myon Kim (Sensors, 2020)

Blade Rub-Impact Fault Identification Using Autoencoder-Based Nonlinear Function Approximation and a Deep Neural Network. - Alexander E. Prosvirin; Farzin Piltan; Jong-Myon Kim (Sensors, 2020)

Bearing Fault Diagnosis of Induction Motors Using a Genetic Algorithm and Machine Learning Classifiers. - Rafia Nishat Toma; Alexander E. Prosvirin; Jong-Myon Kim (Sensors, 2020)

Global and Local Feature Extraction Using a Convolutional Autoencoder and Neural Networks for Diagnosing Centrifugal Pump Mechanical Faults. - Alexander E. Prosvirin; Zahoor Ahmad; Jong-Myon Kim (IEEE Access, 2021)

Novel Bearing Fault Diagnosis Using Gaussian Mixture Model-Based Fault Band Selection. - Andrei S. Maliuk; Alexander E. Prosvirin; Zahoor Ahmad; Cheol Hong Kim; Jong-Myon Kim (Sensors, 2021)

Construction of a Sensitive and Speed Invariant Gearbox Fault Diagnosis Model Using an Incorporated Utilizing Adaptive Noise Control and a Stacked Sparse Autoencoder-Based Deep Neural Network. - Cong Dai Nguyen; Alexander E. Prosvirin; Cheol Hong Kim; Jong-Myon Kim (Sensors, 2021)

Hybrid Rubbing Fault Identification Using a Deep Learning-Based Observation Technique. - Alexander E. Prosvirin; Farzin Piltan; Jong-Myon Kim (IEEE Trans. Neural Networks Learn. Syst., 2021)

Intelligent rubbing fault identification using multivariate signals and a multivariate one-dimensional convolutional neural network. - Alexander E. Prosvirin; Andrei S. Maliuk; Jong-Myon Kim (Expert Syst. Appl., 2022)