EMC Lab

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I happen to have discovered a direct relation between magnetism and light, also electricity and light, and the field it opens is so large and I think rich.
Michael Faraday

At FIU low frequency electromagnetic compatibility lab, the electromagnetic signature study of the power network components is implemented. The study is in simulation, as well as experimental phase.

The simulation is implemented by using physics based modeling softwares, such as ANSYS, COMSOL, INFOLYTICA, and MAGSOFT for various applications. The new equivalent source models, such as wire model, optimized cube model, generalized equivalent models and etc. are proposed and published in distinguished journals [1-4]. All of the simulation models are verified experimentally.

plate motor

The models and their experimental setups were utilized for the application of condition monitoring, fault diagnosis, as well as improving the performance of the components. The condition monitoring methods such as current signature, vibration, WFA/MWFA, internal and external search coils, IAs and many other methods are valuable methods in fault diagnosis. But most of them have the lack that they cannot distinguish the unbalanced voltage from the short-circuit in windings. Through the electromagnetic signature method, this two faults can be separated from each other [5]. In addition to the fault-type detection, the location of incipient faults is also identified [6].

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In addition, the switching algorithm of the converter is investigated for different purposes using the electromagnetic signatures [7]. The diagnosis of the faulty components in between similar or different components in the network is also implemented using both magnetic and electric signature analysis with the help of digital signal processing techniques.

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References:

  1. M.R Barzegaran, O.A. Mohammed, “Multi-Dipole Modeling of XLPE Cable for Electromagnetic Field Studies in Large Power Systems,” International Journal for Comp. and Math. in Electrical Eng. (COMPEL), vol. 33, No. 1, 2014.
  2. Ali Sarikhani, M. Barzegaran, O. A. Mohammed, “Optimum Equivalent Models of Multi-source Systems for the Study of Electromagnetic Signatures and radiated Emissions from Electric Drives,” IEEE Transaction on Magnetics, Vol. 48, Issue 2, pp. 1011-1014, 2012.
  3. M.R Barzegaran, O.A. Mohammed, “A Generalized Equivalent Source Model of AC Electric Machines for Numerical Electromagnetic Field Signature Studies,” IEEE Transaction on Magnetics, Vol. 48, No. 11, Nov 2012.
  4. M.R Barzegaran, Ali Sarikhani, Osama A. Mohammed, “An Optimized Equivalent Source Modeling for the Evaluation of Time Harmonic Radiated Fields from Electrical Machines and Drives” Applied Computational Electromagnetics Society Journal, Vol. 28, No. 4, pp. 273-282, Apr. 2013.
  5. M.R Barzegaran, Ali Mazloomzadeh, O.A. Mohammed “Fault Diagnosis of the Asynchronous Machines through Magnetic Signature Analysis using Finite Element Method and Neural Networks,” IEEE Transaction on Energy Conversion, Vol 28, No. 4, pp. 1064-1071, DEC 2013
  6. M.R Barzegaran, A. Mazloomzadeh, O.A. Mohammed, “Identification of Short-circuit Location in Induction Motors using Radiated Electromagnetic Field Signatures,” Accepted to be presented at International Conference on Electrical Machines and Systems (ICEMS 2013), Korea.
  7. M.R Barzegaran, Ahmed Mohamed, Tarek Yussef, O.A. Mohammed “Electromagnetic signature study of the power converter connected to an electric motor drives,” IEEE Transaction on Magnetics [In Press].
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