Szczegóły

Tytuł artykułu

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

Tytuł czasopisma

Archives of Control Sciences

Rocznik

2010

Numer

No 3

Autorzy publikacji

Wydział PAN

Nauki Techniczne

Wydawca

Committee of Automatic Control and Robotics PAS

Data

2010

Identyfikator

ISSN 1230-2384

Referencje

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

×