S. E. Zouzou

Dynamic eccentricity in squirrel cage induction motors – Simulation and analytical study of its spectral signatures on stator currents

Most of faults in three-phase induction motors have relationship with airgap eccentricity. There are two forms of airgap eccentricity: static (SE) and dynamic (DE). According to the literatures, the well known signatures of dynamic eccentricity, on the stator current spectra, are sidebands around the principal slot harmonics (PSH). However, many other researches have shown that DE induces also spectral components around the fundamental, but few are reported on the sources and the causes of these components. In this direction and since it is difficult to study experimentally the DE separately from the SE; the present paper attempts to explain, analytically and by simulation, the generation process of all frequency components that are a function of only DE. For that reason, a detailed analytical study for three-phase induction motors working under DE is performed. This study is based on rotating field approach. A general theoretical analysis of the interaction between all harmonics of the eccentric airgap permeance and the stator and rotor MMF components is put forward. The simulation results, obtained from an accurate model, confirm the existence of specific frequency components around the fundamental, caused by the dynamic airgap eccentricity. The interactions between the DE and the inherent SE are also illustrated using this mathematical model.

Induction motors airgap-eccentricity detection through the discrete wavelet transform of the apparent power signal under non-stationary operating conditions

Fast Fourier transform (FFT) analysis has been successfully used for fault diagnosis in induction machines. However, this method does not always provide good results for the cases of load torque, speed and voltages variation, leading to a variation of the motor-slip and the consequent FFT problems that appear due to the non-stationary nature of the involved signals. In this paper, the discrete wavelet transform (DWT) of the apparent-power signal for the airgap-eccentricity fault detection in three-phase induction motors is presented in order to overcome the above FFT problems. The proposed method is based on the decomposition of the apparent-power signal from which wavelet approximation and detail coefficients are extracted. The energy evaluation of a known bandwidth permits to define a fault severity factor (FSF). Simulation as well as experimental results are provided to illustrate the effectiveness and accuracy of the proposed method presented even for the case of load torque variations.

Considerations about the modeling and simulation of air-gap eccentricity in induction motors

This paper proposes, firstly, a precise evaluation of the inductances of induction machine (IM) by transforming the calculations into a simple calculation of surfaces. The skewing bars effect and linear rise of the magneto-motive force (MMF) across the slot in case of constant or nonuniform air-gap are taken into account. Secondly, we consider the two types of star stator winding coupling of IM, YN-connected and Y-connected. The choice of a 2-pole IM in our application is due to the fact that the majority of the previous publications have used a 4-pole IM or more. Also, and particularly, the 2-pole IM can have homopolar flux in presence of eccentricity or odd number of slots per pole. It is the reason for which it deserves a particular interest. The model is established initially in case of symmetric machine, then, in the frequent case of radial eccentricity which is the mixed eccentricity. This objective would be achieved by exploiting an extension in 2-D of the modified winding function approach (MWFA). The analysis is validated by comparing the experimental line-current spectra of the eccentric machine to the simulation results

Induction Motors Broken Rotor Bars Diagnosis Through the Discrete Wavelet Transform of the Instantaneous Reactive Power Signal under Time-varying Load Conditions

Abstract—In this article, a method based on the application of the discrete wavelet transform to the instantaneous reactive power signal, for diagnosing the occurrence of broken rotor bars in induction motors operating under time-varying load conditions, is presented. This method is based on the decomposition of the instantaneous reactive power signal, from which wavelet approximation and detail coefficients are extracted. The energy evaluation of known bandwidths permits to define a fault severity factor. This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. These simulation results are complemented by experimental tests conducted on an induction motor with several faulty rotors that can be interchanged and both simulation and experimental results have shown the effectiveness of the proposed method for broken rotor bars diagnosis in induction motors even under time-varying load conditions.

Static eccentricity fault diagnosis using the signatures analysis of stator current and air gap magnetic flux by finite element method in saturated induction motors

Static eccentricity produces low frequency air gap flux components, however they can be observed in stator current spectrum only under mixed eccentricity, and for high degrees of rotor shifting. Unlike motor current signature analysis, the air-gap magnetic flux signature analysis allows to detect small degree of purely static eccentricity. The simulation results are obtained by using time stepping finite elements method. In order to indicate the influence of the magnetic saturation upon the analysis of the faulty induction motor, two constant and non-liner permeability; are included in this paper. It is shown that the fault index amplitudes of obtained signals from the constant permeability are larger than that of the real case. In this paper the amplitudes of characteristic frequency components

Broken rotor bars diagnosis in an induction motor fed from a frequency converter: experimental research

f_{ecc} = \left| {f_{s} \pm k{\kern 1pt} f_{r} } \right|

Application of the convolution theorem for the modeling of saturated induction motors

fecc=|fs±kfr| with low degrees of purely static eccentricity fault are detected using air-gap magnetic flux signature analysis. Moreover, new index signatures are detected around the third time harmonics in air-gap magnetic flux density spectrum for saturated motor, those components are expressed by