Alexander E. Prosvirin

Orcid: 0000-0002-7943-5845

According to our database1, Alexander E. Prosvirin authored at least 17 papers between 2017 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2022
Intelligent rubbing fault identification using multivariate signals and a multivariate one-dimensional convolutional neural network.
Expert Syst. Appl., 2022

2021
Hybrid Rubbing Fault Identification Using a Deep Learning-Based Observation Technique.
IEEE Trans. Neural Networks Learn. Syst., 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.
Sensors, 2021

Novel Bearing Fault Diagnosis Using Gaussian Mixture Model-Based Fault Band Selection.
Sensors, 2021

Global and Local Feature Extraction Using a Convolutional Autoencoder and Neural Networks for Diagnosing Centrifugal Pump Mechanical Faults.
IEEE Access, 2021

2020
Bearing Fault Diagnosis of Induction Motors Using a Genetic Algorithm and Machine Learning Classifiers.
Sensors, 2020

Blade Rub-Impact Fault Identification Using Autoencoder-Based Nonlinear Function Approximation and a Deep Neural Network.
Sensors, 2020

A Reliable Fault Diagnosis Method for a Gearbox System with Varying Rotational Speeds.
Sensors, 2020

Robot manipulator active fault-tolerant control using a machine learning-based automated robust hybrid observer.
J. Intell. Fuzzy Syst., 2020

Multistage Centrifugal Pump Fault Diagnosis by Selecting Fault Characteristic Modes of Vibration and Using Pearson Linear Discriminant Analysis.
IEEE Access, 2020

Fault Identification of Multi-level Gear Defects Using Adaptive Noise Control and a Genetic Algorithm.
Proceedings of the Intelligent Human Computer Interaction, 2020

2019
An Improved Algorithm for Selecting IMF Components in Ensemble Empirical Mode Decomposition for Domain of Rub-Impact Fault Diagnosis.
IEEE Access, 2019

2018
Reliable fault diagnosis of bearings with varying rotational speeds using envelope spectrum and convolution neural networks.
Soft Comput., 2018

Rub-Impact Fault Diagnosis Using an Effective IMF Selection Technique in Ensemble Empirical Mode Decomposition and Hybrid Feature Models.
Sensors, 2018

Intelligent Rub-Impact Fault Diagnosis Based on Genetic Algorithm-Based IMF Selection in Ensemble Empirical Mode Decomposition and Diverse Features Models.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2018, 2018

Towards bearing health prognosis using generative adversarial networks: Modeling bearing degradation.
Proceedings of the International Conference on Advancements in Computational Sciences, 2018

2017
Bearing Fault Diagnosis Based on Convolutional Neural Networks with Kurtogram Representation of Acoustic Emission Signals.
Proceedings of the Advances in Computer Science and Ubiquitous Computing, 2017


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