Details

Title

Stator inter-turn fault detection of an induction motor using neuro-fuzzy techniques

Journal title

Archives of Control Sciences

Yearbook

2010

Numer

No 3

Publication authors

Divisions of PAS

Nauki Techniczne

Description

Archives of Control Sciences welcomes for consideration papers on topics of significance in broadly understood control science and related areas, including: basic control theory, optimal control, optimization methods, control of complex systems, mathematical modeling of dynamic and control systems, expert and decision support systems and diverse methods of knowledge modelling and representing uncertainty (by stochastic, set-valued, fuzzy or rough set methods, etc.), robotics and flexible manufacturing systems. Related areas that are covered include information technology, parallel and distributed computations, neural networks and mathematical biomedicine, mathematical economics, applied game theory, financial engineering, business informatics and other similar fields.

Aims and Scope: Archives of Control Sciences publishes papers in the broadly understood field of control science and related areas while promoting the closer integration of the Polish, as well as other Central and East European scientific communities with the international world of science.

Publisher

Committee of Automatic Control and Robotics PAS

Date

2010

Identifier

ISSN 1230-2384

References

Arkan M. (2005), Modelling and simulation of induction motors with inter-turn faults for diagnosis, Electric Power Systems Research, 75, 57. ; Bachir S. (2006), Diagnosis by parameter estimation of stator and rotor faults occurring in induction machines, IEEE Trans. Ind. Electron, 53, 3, 963. ; Riera-Guasp M. (2008), The use of the wavelet approximation signal as a tool for the diagnosis and quantification of rotor bar failures, IEEE Trans. Ind. Appl, 44, 3, 716. ; A. da Silva (2008), Induction machine broken bar and stator short-circuit fault diagnostics based on three-phase stator current envelope, IEEE Trans. Ind. Electron, 55, 3, 1310. ; Yen G. (2000), Wavelet packet feature extraction for vibration monitoring, IEEE Trans. Ind. Electron, 47, 3, 650. ; Benbouzid M. (1999), Induction motors' detection and localization using stator current advanced signal processing techniques, IEEE Trans. Power Electron, 14, 1, 14. ; Chow T. (2004), Induction machine fault diagnostic analysis with wavelet technique, IEEE Trans. Ind. Electron, 51, 3, 558. ; Thomson W. (2001), Current signature analysis to detect induction motor faults, IEEE Ind. Appl. Mag, 7, 4, 26. ; Nandi S. (2000), Novel frequency domain based technique to detect incipient stator inter-turn faults in induction machines, null, 367. ; Arthur N. (2000), Induction machine condition monitoring with higher order spectra, IEEE Trans. Ind. Electron, 47, 5, 1031. ; Bouzid M. (2008), An effective neural approach for the automatic location of stator interturn faults in induction motor, IEEE Trans. Ind. Electron, 55, 12, 4277. ; Rodríguez P. (2008), Detection of stator winding fault in induction motor using fuzzy logic, Applied Soft Computing, 8, 2, 1112. ; Ballal M. (2007), Adaptive neural fuzzy inference system for the detection of inter-turn insulation and bearing wear faults in induction motor, IEEE Trans. Ind. Electron, 54, 1, 250. ; Awadallah M. (2003), Application of AI tools in fault diagnosis of electrical machines and drives Ů- An overview, IEEE Trans. Energy Convers, 18, 2, 245. ; Uraikul V. (2007), Artificial intelligence for monitoring and supervisory control of process systems, Eng. Appl. Artif. Intell, 20, 2, 115. ; Filippetti F. (2008), AI techniques in induction machines diagnosis including the speed ripple effect, IEEE Trans. Ind. Appl, 34, 1, 98. ; Filippetti F. (2000), Recent developments of induction motor drives fault diagnosis using AI techniques, IEEE Trans. Ind. Electron, 47, 5, 994. ; Hong S. (2005), Neural-network-based sensor fusion of optical emission and mass spectroscopy data for real-time fault detection in reactive ion etching, IEEE Trans. Ind. Electron, 52, 4, 1063. ; Altug S. (2008), Fuzzy inference system implemented on neural architectures for motor fault detection and diagnosis, IEEE Trans. Ind. Electron, 46, 6, 1069.

DOI

10.2478/v10170-010-0022-7

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