Study on fault diagnosis of broken rotor bars in squirrel cage induction motors: a multi‐agent system approach using intelligent classifiers
暂无分享,去创建一个
Panagiotis Tzionas | Maria Drakaki | Yannis L. Karnavas | Ioannis D. Chasiotis | Athanasios Karlis | Y. L. Karnavas | I. Chasiotis | P. Tzionas | A. Karlis | M. Drakaki
[1] A. H. Bonnett,et al. Analysis of rotor failures in squirrel-cage induction motors , 1988 .
[2] Osman Bilgin,et al. Automatic detection and classification of rotor cage faults in squirrel cage induction motor , 2010, Neural Computing and Applications.
[3] Richard J. Povinelli,et al. Induction Machine Broken Bar and Stator Short-Circuit Fault Diagnostics Based on Three-Phase Stator Current Envelopes , 2008, IEEE Transactions on Industrial Electronics.
[4] Gérard-André Capolino,et al. High Frequency Resolution Techniques for Rotor Fault Detection of Induction Machines , 2008, IEEE Transactions on Industrial Electronics.
[5] Jawad Faiz,et al. A survey on time and frequency characteristics of induction motors with broken rotor bars in line-start and inverter-fed modes , 2015 .
[6] Chee Peng Lim,et al. Condition monitoring of induction motors: A review and an application of an ensemble of hybrid intelligent models , 2014, Expert Syst. Appl..
[7] Alessandro Goedtel,et al. Stator fault analysis of three-phase induction motors using information measures and artificial neural networks , 2017 .
[8] David W. L. Wang,et al. Toward a systems- and control-oriented agent framework , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[9] Barry W. Williams,et al. Induction motor broken rotor bar fault detection techniques based on fault signature analysis – a review , 2018 .
[10] Adam Glowacz,et al. Diagnosis of stator faults of the single-phase induction motor using acoustic signals , 2017 .
[11] Paulo Leitão,et al. Past, Present, and Future of Industrial Agent Applications , 2013, IEEE Transactions on Industrial Informatics.
[12] H.A. Toliyat,et al. Condition Monitoring and Fault Diagnosis of Electrical Motors—A Review , 2005, IEEE Transactions on Energy Conversion.
[13] Salil S. Kanhere,et al. Multi-Agent Systems: A Survey , 2018, IEEE Access.
[14] Jyh-Shing Roger Jang,et al. ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..
[15] Peter E. Hart,et al. Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.
[16] Fiorenzo Filippetti,et al. Recent developments of induction motor drives fault diagnosis using AI techniques , 2000, IEEE Trans. Ind. Electron..
[17] S. E. Zouzou,et al. Induction motor broken rotor bars detection using fuzzy logic: experimental research , 2014, Int. J. Syst. Assur. Eng. Manag..
[18] Alessandro Goedtel,et al. Diagnosis of Stator Faults Severity in Induction Motors Using Two Intelligent Approaches , 2017, IEEE Transactions on Industrial Informatics.
[19] J. Faiz,et al. A New Pattern for Detecting Broken Rotor Bars in Induction Motors During Start-Up , 2008, IEEE Transactions on Magnetics.
[20] Alessandro Goedtel,et al. A comprehensive evaluation of intelligent classifiers for fault identification in three-phase induction motors , 2015 .
[21] Vilas N. Ghate,et al. Cascade Neural-Network-Based Fault Classifier for Three-Phase Induction Motor , 2011, IEEE Transactions on Industrial Electronics.
[22] Panagiotis Tzionas,et al. Modeling and performance evaluation of an agent-based warehouse dynamic resource allocation using Colored Petri Nets , 2016, Int. J. Comput. Integr. Manuf..
[23] Paulo Leitão,et al. Agent-based distributed manufacturing control: A state-of-the-art survey , 2009, Eng. Appl. Artif. Intell..
[24] Adam Glowacz,et al. Acoustic based fault diagnosis of three-phase induction motor , 2018, Applied Acoustics.
[25] J.R. McDonald,et al. Applying multi-agent system technology in practice: automated management and analysis of SCADA and digital fault recorder data , 2006, 2006 IEEE Power Engineering Society General Meeting.
[26] M. M. Morcos,et al. Application of AI tools in fault diagnosis of electrical machines and drives-an overview , 2003 .
[27] O. Ondel,et al. A method to detect broken bars in induction machine using pattern recognition techniques , 2006, IEEE Transactions on Industry Applications.
[28] Alessandro Goedtel,et al. A novel multi-agent approach to identify faults in line connected three-phase induction motors , 2016, Appl. Soft Comput..
[29] Hubert Razik,et al. A Novel Monitoring of Load Level and Broken Bar Fault Severity Applied to Squirrel-Cage Induction Motors Using a Genetic Algorithm , 2009, IEEE Transactions on Industrial Electronics.
[30] Neerukonda Rama Devi,et al. Detection of stator incipient faults and identification of faulty phase in three-phase induction motor – simulation and experimental verification , 2015 .
[31] Da-wei Hao,et al. MAS-based solution to energy management strategy of distributed generation system , 2015 .
[32] B Bessam,et al. Detection of broken rotor bar faults in induction motor at low load using neural network. , 2016, ISA transactions.
[33] B. Singh,et al. A review of stator fault monitoring techniques of induction motors , 2005, IEEE Transactions on Energy Conversion.
[34] Aurobinda Routray,et al. Fast and accurate spectral estimation for online detection of partial broken bar in induction motors , 2018 .