Sensorless fault diagnosis of induction motors - Networked ...

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Atiya, “Multi-step-ahead predictionin complex systems using dynamic recurrent neural networks,” NeuralNetworks, vol. 13, no. 7, pp. 765–786, Sept. 2000.Kyusung Kim (S’96–M’01) received the B.S. andthe M.S. degrees from Seoul National University,Seoul, Korea, in 1991 and 1993, respectively, and thePh.D. degree from Texas A&M University, CollegeStation, in 2001, all in nuclear engineering.He is currently a Senior Research Scientist withHoneywell Laboratories, Minneapolis, MN. His researchinterests are in the area of information processingand decision making for the condition managementof valuable assets.Alexander G. Parlos (S’81–M’87–SM’92) receivedthe B.S. degree in nuclear engineering from TexasA&M University, College Station, in 1983, and theS.M. degree in mechanical engineering, the S.M.degree in nuclear engineering, and the Sc.D. degreein automatic control and systems engineering fromMassachusetts Institute of Technology, Cambridge,in 1985, 1985, and 1986, respectively.Since 1987, he has been a member of the facultyof Texas A&M University, where he is currently anAssociate Professor of Mechanical Engineering, withjoint appointments in the Department of Nuclear Engineering and Department ofElectrical Engineering. His applied research interests include the developmentof methods and algorithms for life-cycle health and performance management ofvarious dynamic systems, with special emphasis to system condition assessment(or diagnosis), end-of-life prediction (or prognosis), and reconfigurable control.He has been involved with the particular application of these concepts to electromechanicalsystems and more recently to computer networks. His theoreticalresearch interests involve the development of learning algorithms for recurrentneural networks and their use for nonlinear estimation and control. He has beeninvolved with research and teaching in neural networks, multivariable control,and system identification, and he has conducted extensive funded research inthese areas. His research has resulted in one U.S. patent, three pending U.S.patents, and 18 invention disclosures. He has co-founded a high-tech start-upcompany commercializing technology developed at Texas A&M. He has authoredover 135 publications in journals and conferencesDr. Parlos has served as an Associate Editor of the IEEE TRANSACTIONS ONNEURAL NETWORKS since 1994, and of the Journal of Control, Automation andSystems since 1999. He served as a technical reviewer to numerous professionaljournal and government organizations, and he has participated in technical, organizing,and program committees of various conferences. He is a Senior Memberof the American Institute of Aeronautics and Astronautics, a Member of theAmerican Society of Mechanical Engineers, American Nuclear Society, and InternationalNeural Networks Society, and a Registered Professional Engineer inthe State of Texas.Raj Mohan Bharadwaj (S’93–M’01) received theB.Sc (Eng.) degree in electrical engineering fromBhagalpur College of Engineering, Bhagalpur, India,in 1993, the M.Sc. (Eng.) degree in high-voltageengineering from Indian Institute of Science,Bangalore, India, in 1997, and the Ph.D. degree inelectrical engineering from Texas A&M University,College Station, in 2000.In December 2000, he joined the General ElectricGlobal Research Center, Niskayuna, NY, where he iscurrently an Electrical Engineer. His research interestsare in the field of neural networks, sensor networks, fault diagnosis, systemidentification, and system optimization.