NDLI: Detection of rotor faults in torque controlled induction motor drives

Content Provider	IEEE Xplore Digital Library
Author	Cunha, C.C.M. Filho, B.J.C. Lyra, R.O.C.
Copyright Year	2007
Description	Author affiliation: UFES, Vitoria (Cunha, C.C.M.)
Abstract	In the supervision of electrical equipment, the task of diagnostic system is to detect an upcoming machine fault as soon as possible, in order to save expensive manufacturing processes or to replace fault parts. An important issue in such effort is the modelling of the induction machine (IM) including rotor bar and end-ring faults, with a minimum of computational complexity. In this paper, a simpler method is employed in the simulation of an induction motor with rotor asymmetries. Simulation of classical and dynamic space vector models, Finite Element Analysis and experimental results are presented to support the proposed model. The need for detection of rotor faults at an earlier stage has pushed the development of monitoring methods with increasing sensitivity and noise immunity. Addressing diagnostic techniques based on current signatures analysis (MCSA), the characteristic components introduced by specific faults in the current spectrum are investigated and a diagnosis procedure correlates the amplitudes of such components to the fault extent. The impact of feedback control on asymmetric rotor cage induction machine behavior is also analyzed. It is shown that the variables usually employed in diagnosis procedures assuming open-loop operation are no longer effective under closed-loop operation. Simulation results show that signals already present at the drive are suitable to effective diagnostic procedure. The utilization of the current regulator error signals in rotor failure detection are the aim of the present work. The use of a band-pass filter bank to detect the presence of sidebands is also proposed.
Starting Page	1
Ending Page	10
File Size	663189
Page Count	10
File Format	PDF
ISBN	9789275815108
DOI	10.1109/EPE.2007.4417754
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-02
Publisher Place	Denmark
Access Restriction	Subscribed
Rights Holder	EPE Association
Subject Keyword	Induction motors Computational modeling Diagnostics Rotors Electrical fault detection Computational complexity Electrical drive Induction motor drives Induction motor Manufacturing processes Fault detection Simulation Torque control Modelling Induction machines
Content Type	Text
Resource Type	Article

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