Title :
Detection of induction machines anomalies using stand-still tests
Author :
A, Mpanda Mabwe Badileshi ; Cristian, Demian ; Capolino, Gérard-André ; Henao, Humberto
Author_Institution :
ESIEE-Amiens, Amiens, France
Abstract :
The main topic of this paper is to examine the feasibility of detecting the rotor defaults of induction motors by performing stand-still tests. We show that feeding the machine with special excitation signals (discrete interval binary sequence (DIBS) and multisine), it is possible to excite with low frequency resolution the faulty modes by analyzing the current spectrum and the dispersion flux captured by a flux sensor. The method presented is general and may be applied to the induction machine whilst in rotation or at standstill. It is based on broadband excitation signals which are able to excite the faulty modes of devices under tests. Experimental measurements are made both on healthy and faulty machines and the comparison gives a difference in the flux and current machine signatures which is basically the most commonly used method of fault detection.
Keywords :
fault diagnosis; machine testing; magnetic flux; magnetic sensors; magnetic variables measurement; rotors; signal processing; spectral analysis; squirrel cage motors; 18 kW; 380 V; 50 Hz; broadband excitation signals; current machine signatures; current spectrum; discrete interval binary sequence; dispersion flux capture; excitation signals; faulty modes; flux sensor; induction machines anomalies detection; induction motors; low frequency resolution; multisine; rotor defaults detection; squirrel cage motors; stand-still tests; Binary sequences; Current measurement; Frequency; Induction machines; Induction motors; Performance evaluation; Rotors; Signal analysis; Signal resolution; Testing;
Conference_Titel :
Industry Applications Conference, 2003. 38th IAS Annual Meeting. Conference Record of the
Print_ISBN :
0-7803-7883-0
DOI :
10.1109/IAS.2003.1257821