Current-Based Bearing Fault Diagnosis Using Deep Learning Algorithms
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- N. Bessous & S. E. Zouzou & W. Bentrah & S. Sbaa & M. Sahraoui, 2018. "Diagnosis of bearing defects in induction motors using discrete wavelet transform," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(2), pages 335-343, April.
- Tianjun Zhang & Shuang Song & Shugang Li & Li Ma & Shaobo Pan & Liyun Han, 2019. "Research on Gas Concentration Prediction Models Based on LSTM Multidimensional Time Series," Energies, MDPI, vol. 12(1), pages 1-15, January.
- Yuri Merizalde & Luis Hernández-Callejo & Oscar Duque-Perez, 2017. "State of the Art and Trends in the Monitoring, Detection and Diagnosis of Failures in Electric Induction Motors," Energies, MDPI, vol. 10(7), pages 1-34, July.
- Shrinathan Esakimuthu Pandarakone & Yukio Mizuno & Hisahide Nakamura, 2019. "A Comparative Study between Machine Learning Algorithm and Artificial Intelligence Neural Network in Detecting Minor Bearing Fault of Induction Motors," Energies, MDPI, vol. 12(11), pages 1-14, June.
- Peng Qian & Xiange Tian & Jamil Kanfoud & Joash Lap Yan Lee & Tat-Hean Gan, 2019. "A Novel Condition Monitoring Method of Wind Turbines Based on Long Short-Term Memory Neural Network," Energies, MDPI, vol. 12(18), pages 1-15, September.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Tongguang Yang & Guanchen Li & Tongyu Wang & Shengyou Yuan & Xueyin Yang & Xiaoguang Yu & Qingkai Han, 2023. "A Novel 1D-Convolutional Spatial-Time Fusion Strategy for Data-Driven Fault Diagnosis of Aero-Hydraulic Pipeline Systems," Mathematics, MDPI, vol. 11(14), pages 1-21, July.
- Muhammed Ali Gultekin & Ali Bazzi, 2023. "Review of Fault Detection and Diagnosis Techniques for AC Motor Drives," Energies, MDPI, vol. 16(15), pages 1-22, July.
- Tomas Garcia-Calva & Daniel Morinigo-Sotelo & Vanessa Fernandez-Cavero & Rene Romero-Troncoso, 2022. "Early Detection of Faults in Induction Motors—A Review," Energies, MDPI, vol. 15(21), pages 1-18, October.
- Hisahide Nakamura & Yukio Mizuno, 2024. "Identification System for Short-Circuit Fault Points in Concentrated Stator Windings of Motors," Energies, MDPI, vol. 17(9), pages 1-14, April.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Muhammad Zuhaib & Faraz Ahmed Shaikh & Wajiha Tanweer & Abdullah M. Alnajim & Saleh Alyahya & Sheroz Khan & Muhammad Usman & Muhammad Islam & Mohammad Kamrul Hasan, 2022. "Faults Feature Extraction Using Discrete Wavelet Transform and Artificial Neural Network for Induction Motor Availability Monitoring—Internet of Things Enabled Environment," Energies, MDPI, vol. 15(21), pages 1-32, October.
- Xiangrui Meng & Haoqian Chang & Xiangqian Wang, 2022. "Methane Concentration Prediction Method Based on Deep Learning and Classical Time Series Analysis," Energies, MDPI, vol. 15(6), pages 1-15, March.
- Wagner Fontes Godoy & Daniel Morinigo-Sotelo & Oscar Duque-Perez & Ivan Nunes da Silva & Alessandro Goedtel & Rodrigo Henrique Cunha Palácios, 2020. "Estimation of Bearing Fault Severity in Line-Connected and Inverter-Fed Three-Phase Induction Motors," Energies, MDPI, vol. 13(13), pages 1-17, July.
- Muhammad Amir Khan & Bilal Asad & Karolina Kudelina & Toomas Vaimann & Ants Kallaste, 2022. "The Bearing Faults Detection Methods for Electrical Machines—The State of the Art," Energies, MDPI, vol. 16(1), pages 1-54, December.
- Sebastian Berhausen & Tomasz Jarek, 2021. "Method of Limiting Shaft Voltages in AC Electric Machines," Energies, MDPI, vol. 14(11), pages 1-19, June.
- Mitja Nemec & Vanja Ambrožič & Rastko Fišer & David Nedeljković & Klemen Drobnič, 2019. "Induction Motor Broken Rotor Bar Detection Based on Rotor Flux Angle Monitoring," Energies, MDPI, vol. 12(5), pages 1-17, February.
- Cherif, Hakima & Benakcha, Abdelhamid & Laib, Ismail & Chehaidia, Seif Eddine & Menacer, Arezky & Soudan, Bassel & Olabi, A.G., 2020. "Early detection and localization of stator inter-turn faults based on discrete wavelet energy ratio and neural networks in induction motor," Energy, Elsevier, vol. 212(C).
- Ana Rita Nunes & Hugo Morais & Alberto Sardinha, 2021. "Use of Learning Mechanisms to Improve the Condition Monitoring of Wind Turbine Generators: A Review," Energies, MDPI, vol. 14(21), pages 1-22, November.
- Piotr Kołodziejek & Daniel Wachowiak, 2022. "Fast Real-Time RDFT- and GDFT-Based Direct Fault Diagnosis of Induction Motor Drive," Energies, MDPI, vol. 15(3), pages 1-14, February.
- Yuri Vankov & Aleksey Rumyantsev & Shamil Ziganshin & Tatyana Politova & Rinat Minyazev & Ayrat Zagretdinov, 2020. "Assessment of the Condition of Pipelines Using Convolutional Neural Networks," Energies, MDPI, vol. 13(3), pages 1-12, February.
- Camila Paes Salomon & Wilson Cesar Sant’Ana & Germano Lambert-Torres & Luiz Eduardo Borges da Silva & Erik Leandro Bonaldi & Levy Ely de Lacerda De Oliveira, 2018. "Comparison among Methods for Induction Motor Low-Intrusive Efficiency Evaluation Including a New AGT Approach with a Modified Stator Resistance," Energies, MDPI, vol. 11(4), pages 1-21, March.
- Bing Liu & Jichong Lei & Jinsen Xie & Jianliang Zhou, 2022. "Development and Validation of a Nuclear Power Plant Fault Diagnosis System Based on Deep Learning," Energies, MDPI, vol. 15(22), pages 1-15, November.
- Arkadiusz Duda & Maciej Sułowicz, 2020. "A New Effective Method of Induction Machine Condition Assessment Based on Zero-Sequence Voltage (ZSV) Symptoms," Energies, MDPI, vol. 13(14), pages 1-26, July.
- Jordi Burriel-Valencia & Ruben Puche-Panadero & Javier Martinez-Roman & Angel Sapena-Baño & Martin Riera-Guasp & Manuel Pineda-Sánchez, 2019. "Multi-Band Frequency Window for Time-Frequency Fault Diagnosis of Induction Machines," Energies, MDPI, vol. 12(17), pages 1-18, August.
- Angel Arranz-Gimon & Angel Zorita-Lamadrid & Daniel Morinigo-Sotelo & Oscar Duque-Perez, 2021. "A Review of Total Harmonic Distortion Factors for the Measurement of Harmonic and Interharmonic Pollution in Modern Power Systems," Energies, MDPI, vol. 14(20), pages 1-38, October.
- Maksymilian Mądziel, 2023. "Future Cities Carbon Emission Models: Hybrid Vehicle Emission Modelling for Low-Emission Zones," Energies, MDPI, vol. 16(19), pages 1-16, October.
- Souradeep Chakraborty, 2019. "Capturing Financial markets to apply Deep Reinforcement Learning," Papers 1907.04373, arXiv.org, revised Dec 2019.
- Shuang Song & Shugang Li & Tianjun Zhang & Li Ma & Shaobo Pan & Lu Gao, 2021. "Research on a Multi-Parameter Fusion Prediction Model of Pressure Relief Gas Concentration Based on RNN," Energies, MDPI, vol. 14(5), pages 1-18, March.
- Ravi Kumar Pandit & Davide Astolfi & Isidro Durazo Cardenas, 2023. "A Review of Predictive Techniques Used to Support Decision Making for Maintenance Operations of Wind Turbines," Energies, MDPI, vol. 16(4), pages 1-17, February.
- Mateusz Dybkowski & Szymon Antoni Bednarz, 2019. "Modified Rotor Flux Estimators for Stator-Fault-Tolerant Vector Controlled Induction Motor Drives," Energies, MDPI, vol. 12(17), pages 1-21, August.
More about this item
Keywords
bearing diagnosis; early damage detection; unlabeled learning; deep learning; dynamic information fusion;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:9:p:2509-:d:544655. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.