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Online parameter estimation and loss calculation using duplex neural — Lumped parameter thermal network for faulty induction motor
- Source :
- 2016 IEEE Conference on Electromagnetic Field Computation (CEFC).
- Publication Year :
- 2016
- Publisher :
- IEEE, 2016.
-
Abstract
- A stator winding fault in one phase of induction motor (IM) gives rise to higher harmonics distortion, increased torque ripple, temperature rise in the magnetic material, mechanical vibrations due to varying magnetic forces and magnetic noise. The fault leads to a change in the electromagnetic field generated in the motor as compared to the normal operation of motor. The copper losses generated in stator increases, thus leading to overall increase in the temperature of the motor. Looking from the aspect of electrical equivalent circuit model, the parameters of the motor changes due the occurrence of fault, which makes it difficult for designing a drive for the motor. In this paper a novel computational model has been presented which uses both artificial neural network model (ANN) and lumped parameter thermal network (LPTN) for parameter estimation and calculation of losses which can be used for designing a fault-tolerant, loss minimizing drive. This dual network model has been and experimented on a 7.5 hp aluminum-rotor induction motor.
- Subjects :
- Electromagnetic field
0209 industrial biotechnology
Engineering
Stator
business.industry
Squirrel-cage rotor
020208 electrical & electronic engineering
02 engineering and technology
Wound rotor motor
law.invention
Quantitative Biology::Subcellular Processes
020901 industrial engineering & automation
Control theory
law
Harmonics
0202 electrical engineering, electronic engineering, information engineering
Equivalent circuit
Torque ripple
business
Simulation
Induction motor
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2016 IEEE Conference on Electromagnetic Field Computation (CEFC)
- Accession number :
- edsair.doi...........c2dd68f7e521276d8ef9ebeae2542a80