Title :
Application of the Teager–Kaiser Energy Operator to the Fault Diagnosis of Induction Motors
Author :
Pineda-Sanchez, M. ; Puche-Panadero, R. ; Riera-Guasp, M. ; Perez-Cruz, J. ; Roger-Folch, J. ; Pons-Llinares, Joan ; Climente-Alarcon, Vicente ; Antonino-Daviu, J.A.
Author_Institution :
Inst. de Ing. Energetica, Univ. Politec. de Valencia, Valencia, Spain
Abstract :
The diagnosis of induction motors through the spectral analysis of the stator current allows for the online identification of different types of faults. One of the major difficulties of this method is the strong influence of the mains component of the current, whose leakage can hide fault harmonics, especially when the machine is working at very low slip. In this paper, a new method for demodulating the stator current prior to its spectral analysis is proposed, using the Teager-Kaiser energy operator. This method is able to remove the mains component of the current with an extremely low usage of computer resources, because it operates just on three consecutive samples of the current. Besides, this operator is also capable of increasing the signal-to-noise ratio of the spectrum, sharpening the spectral peaks that reveal the presence of the faults. The proposed method has been deployed to a PC-based offline diagnosis system and tested on commercial induction motors with broken bars, mixed eccentricity, and single-point bearing faults. The diagnostic results are compared with those obtained through the conventional motor current signature analysis method.
Keywords :
fault diagnosis; induction motors; machine bearings; stators; PC-based offline diagnosis; Teager-Kaiser energy operator; broken bars; computer resources; fault diagnosis; induction motors; mixed eccentricity; motor current; signal-to-noise ratio; signature analysis; single-point bearing faults; spectral analysis; stator current; Circuit faults; Fault diagnosis; Harmonic analysis; Induction motors; Signal analysis; Bearing faults; Teager–Kaiser algorithm; broken-bar rotor faults; demodulation; eccentricity faults; fault diagnosis; induction motor; motor current signature analysis; signal analysis;
Journal_Title :
Energy Conversion, IEEE Transactions on
DOI :
10.1109/TEC.2013.2279917