Results 101 to 110 of about 1,232 (132)

Prediction of induction motor faults using machine learning. [PDF]

Heliyon
Abdulkareem A, Anyim T, Popoola O, Abubakar J, Ayoade A.   +4 more
europepmc   +1 more source

Concurrent Incipient Fault Diagnosis in Three-Phase Induction Motors Using Discriminative Band Energy Analysis of AM-Demodulated Vibration Envelopes. [PDF]

Sensors (Basel)
de Godoy MB, Lucas GB, Andreoli AL.
europepmc   +1 more source

Comprehensive Fault Diagnosis of Three-Phase Induction Motors Using Synchronized Multi-Sensor Data Collection. [PDF]

Sci Data
Thomas K, Rahman A, Rohouma W, Ahamed MF, Shafi FB, Nahiduzzaman M, Khandakar A.   +6 more
europepmc   +1 more source

Electrical signals dataset from fixed-speed and variable-speed synchronous generators under healthy and faulty conditions. [PDF]

Data Brief
Tominaga RN, Sousa LA, Rocha RV, Monaro RM, Ávila SL, Salles MBC, Carmo BS.   +6 more
europepmc   +1 more source

MEPs elicited by multidirectional rotational-field TMS show marked differences compared to unidirectional Figure-of-8 and H7 coils. [PDF]

PLoS One
Wonderman Bar Sela O, Ofir Geva S, Pell GS, Roth Y, Friedman J, Muhana A, Frenkel-Toledo S, Soroker N.   +7 more
europepmc   +1 more source

Structural Design and Electromagnetic Performance Analysis of Octupole Active Radial Magnetic Bearing. [PDF]

Sensors (Basel)
Zhu Q, Lu Y, Shao Z.
europepmc   +1 more source

Study on working mechanism and control method of new magnetic suspension gripper. [PDF]

Sci Rep
Zhu L, Wu X.
europepmc   +1 more source

Motor Fault Diagnosis Based on Convolutional Block Attention Module-Xception Lightweight Neural Network. [PDF]

Entropy (Basel)
Xie F, Fan Q, Li G, Wang Y, Sun E, Zhou S.   +5 more
europepmc   +1 more source

Condition Monitoring of In-Service DFIGs Working Under Non-Stationary Conditions via NsHOTA: A Motor Current Signature Approach. [PDF]

Sensors (Basel)
Delfa-Baena S, Artigao E, Terron-Santiago C, Honrubia-Escribano A, Burriel-Valencia J, Gomez-Lazaro E.   +5 more
europepmc   +1 more source

Hybrid physics-informed artificial intelligence for high-fidelity modeling and optimization of electrical systems. [PDF]

Front Artif Intell
Nyangon J.
europepmc   +1 more source