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240202 ||| eng |
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|a 9783036593975
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|a 9783036593968
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|a books978-3-0365-9396-8
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1 |
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|a He, Yuling
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| 245 |
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|a Condition Monitoring and Failure Prevention of Electric Machines
|h Elektronische Ressource
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| 260 |
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|a Basel
|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2023
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| 300 |
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|a 1 electronic resource (204 p.)
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| 653 |
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|a Energy industries and utilities / bicssc
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| 653 |
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|a efficiency
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| 653 |
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|a in situ efficiency
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| 653 |
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|a condition monitoring
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| 653 |
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|a hybrid surrogate model
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| 653 |
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|a induction motors
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| 653 |
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|a genetic algorithm
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| 653 |
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|a short-circuited turns
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| 653 |
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|a contrast estimation
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| 653 |
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|a harmonic component
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| 653 |
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|a RBF
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| 653 |
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|a field-oriented control
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| 653 |
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|a circulating current inside parallel branches (CCPB)
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| 653 |
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|a pulse-jet cleaning
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| 653 |
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|a History of engineering and technology / bicssc
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| 653 |
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|a deep neural network
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| 653 |
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|a radial dynamic air-gap eccentricity (RDAGE)
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| 653 |
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|a whole load region
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| 653 |
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|a long short-term memory (LSTM) network
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| 653 |
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|a hydro-turbine modeling
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| 653 |
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|a turn-to-turn short circuit
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| 653 |
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|a high resistance connection
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| 653 |
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|a Technology: general issues / bicssc
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| 653 |
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|a rotor slot harmonics frequencies
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| 653 |
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|a unbalanced load flows
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| 653 |
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|a direct torque control
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| 653 |
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|a hydropower
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| 653 |
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|a dynamic modeling
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| 653 |
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|a transient processes
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| 653 |
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|a mathematical modeling
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| 653 |
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|a water flow inertia
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| 653 |
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|a linear motor feeding system
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| 653 |
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|a power supply systems
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| 653 |
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|a line start permanent magnet assisted synchronous reluctance motor
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| 653 |
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|a semi-supervised anomaly detection generative adversarial network (GANomaly)
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| 653 |
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|a radial hybrid air-gap eccentricity (RHAGE)
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| 653 |
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|a radial static air-gap eccentricity (RSAGE)
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| 653 |
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|a Kriging
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| 653 |
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|a parameter identification
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| 653 |
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|a demagnetization
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| 653 |
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|a doubly fed induction generator (DFIG)
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| 653 |
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|a symmetrical components
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| 653 |
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|a electromagnetic torque (EMT)
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| 653 |
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|a QPSO-TRA
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| 653 |
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|a transformer fault
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| 653 |
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|a lack of abnormal samples
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| 653 |
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|a unbalanced load
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| 653 |
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|a dynamic rotor interturn short circuit (DRISC)
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| 653 |
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|a performance optimization
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| 653 |
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|a fault diagnosis
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| 653 |
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|a eccentricity
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| 653 |
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|a synchronous generator
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| 653 |
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|a vibroacoustic signals
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| 653 |
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|a hydropower plants
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| 653 |
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|a artificial neural networks
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| 653 |
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|a magneto-motive force (MMF)
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| 653 |
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|a quantum particle swarm optimization
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| 653 |
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|a anomaly detection
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| 653 |
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|a trust region algorithm
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| 653 |
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|a power factor curve valley
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| 653 |
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|a permanent magnet synchronous machine
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| 653 |
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|a field oriented control
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| 653 |
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|a supervised classification
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| 700 |
1 |
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|a Gerada, David
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| 700 |
1 |
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|a Ma, Conggan
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| 700 |
1 |
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|a Zhao, Haisen
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
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| 028 |
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|a 10.3390/books978-3-0365-9396-8
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| 856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/128768
|z DOAB: description of the publication
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| 856 |
4 |
0 |
|u https://www.mdpi.com/books/pdfview/book/8233
|7 0
|x Verlag
|3 Volltext
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|a 333
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|a This is a reprint of a Special Issue of Energies, titled "Condition Monitoring and Failure Prevention of Electric Machines". This Special Issue primarily focused on the issues related to the advanced monitoring, diagnosis, and prevention of typical and complex faults in all kinds of electric machines. Four guest editors, namely Prof. Yu-Ling He (Department of Mechanical Engineering, North China Electric Power University, China), Prof. David Gerada (PEMC group, University of Nottingham, UK), Prof. Conggan Ma (School of Automotive Engineering, Harbin Institute of Technology, China), and Prof. Haisen Zhao (School of Electrical and Electronics Engineering, North China Electric Power University, China), worked together on this Special Issue.
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