Mohamed Sahraoui

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.

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

The Use of the Modified Prony’s Method for Rotor Speed Estimation in Squirrel-Cage Induction Motors

It is well known that rotor speed estimation assumes a paramount importance for the correct diagnosis of bearings, air-gap eccentricities, or rotor bar defects. In this paper, a new technique for rotor speed estimation using a modified Prony’s method is proposed. The algorithm developed for this purpose is based on tracking the frequencies of the rotor slot harmonics (RSH) that exist in stator currents of most squirrel-cage induction motors. High-order RSH frequencies are used to avoid the possible effect of harmonics stemming from other sources. The proposed modified Prony’s method shows a great ability for tracking RSH frequencies and then the rotation speed. In addition, this technique can deal with noisy and nonstationary signals and it requires only few data samples, which reduce considerably the computational time and data storage requirements. Consequently, the proposed algorithm is suitable for online implementation. The method’s effectiveness is verified by simulation and experimental tests.

Analysis of induction motor with broken rotor bars using finite element method

The paper presents the use of the two-dimensional finite element method for modelling the three-phase squirrel-cage induction motor by using circuit-field coupled method. In order to analyze the machine performances, the voltage source is considered. The flux 2D magnetic analysis software is used for calculating the magnetic field of an induction motor having a cage fault. The simulation results of transient and steady state are given, which verifies the reliability of this method. The experimental results prove that the proposed approach constitutes a useful tool for the study and diagnostics of induction motors.

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

This paper proposes a new method for inductance calculation of induction motors (IM) based on the convolution theorem. The integral form leading to the inductance expressions is derived from the 2D modified winding function approach (2D-MWFA). As first application, a model allowing teeth saturation to be taken into account by the corresponding air-gap permeance variation is proposed. The work points out that appropriate arrangements make it possible to use convolution theorem in favor of integral calculation leading to IM inductances. It is shown that the implication of the convolution concept in such a task reduces strongly the calculation process. Moreover, this method proves to be faster than integrations based on conventional methods. Simulation and experimental results confirm the performance and utility of the proposed technique.

The use of the modified Prony's method for rotor speed estimation in squirrel cage induction motors

It is well known that rotor speed estimation assumes a paramount importance for the correct diagnosis of bearings, air-gap eccentricities, or rotor bar defects. In this paper, a new technique for rotor speed estimation using a modified Pronys method is proposed. The algorithm developed for this purpose is based on tracking the frequencies of the rotor slot harmonics (RSH) that exist in stator currents of most squirrel-cage induction motors. High-order RSH frequencies are used to avoid the possible effect of harmonics stemming from other sources. The proposed modified Pronys method shows a great ability for tracking RSH frequencies and then the rotation speed. In addition, this technique can deal with noisy and nonstationary signals and it requires only few data samples, which reduce considerably the computational time and data storage requirements. Consequently, the proposed algorithm is suitable for online implementation. The methods effectiveness is verified by simulation and experimental tests.

A Fast Inductance Computation Devoted to the Modeling of Healthy, Eccentric, and Saturated Induction Motors

Abstract This work deals with a detailed method for the calculation of induction motor inductances based on the convolution theorem. The integral form leading to the inductance expressions is derived from the 2D modified winding function approach, which takes into account the space harmonics, slot skewing, and radial and axial air-gap eccentricities. As first applications, a model is presented that allows teeth saturation to be taken into account by the corresponding air-gap permeance variation. Next, the idea is adapted to the rotor eccentricity modeling. It is shown that appropriate arrangements make it possible to use the convolution theorem for fast calculation of the inductances. The proposed method proves to be competitive compared to the conventional techniques of integration and even those employing equivalent analytical expressions. To demonstrate the effectiveness of the new proposed methodology, simulation tests based on the multiple coupled circuit model, experimental spectra, as well as time processing verification on a personal computer, are provided.

The use of a modified Prony's method to detect the airgap-eccentricity occurrence in induction motors

Induction motors airgap-eccentricity fault detection has attracted the interest of many researchers in last decades. The Discrete Fourier Transform (DFT) has been widely used for that purpose. However, DFT can only give meaningful information for stationary signals. In this paper, an efficient time-domain technique based on a modified Pronys method for the airgap-eccentricity fault detection in induction motors is presented in order to overcome the DFT problems. Using this technique, the apparent power, as processed signal, is divided into short overlapped time windows, and each one is analyzed by the Least Squares Pronys method. The proposed technique allows tracking the frequencies and amplitudes of the airgap-eccentricity fault characteristic frequency component fr with a very high accuracy. A fault severity factor (FSF) based on fr amplitudes is defined. Simulation as well as experimental results are provided to illustrate the effectiveness and accuracy of the proposed method.

The use of a modified Prony's method to track the broken rotor bars characteristic frequencies and amplitudes, in three-phase induction motors

The knowledge of the broken rotor bar characteristic frequencies and amplitudes has a great importance for all related diagnostic methods. The monitoring of motor faults requires a high resolution spectrum to separate different frequency components. The discrete Fourier transform (DFT) has been widely used to achieve these requirements. However, DFT can give meaningful information only for stationary harmonics which cannot be guaranteed in real cases. In addition, a long data sequence is necessary for DFT to get high frequency resolution. Nevertheless, the signals are time varying, and the steady-state conditions can be lost for a long time acquisition. As a solution for these problems, this paper proposes an efficient time-domain technique based on a modified Prony method for the estimation of the frequencies/amplitudes of broken rotor bar faults. Using this technique, the stator current is divided into short overlapped time windows, and each one is analyzed by the least squares Prony method. The proposed technique provides a linear time-frequency/amplitude representation with high frequency resolution and adjustable time resolution. It is shown that this technique allows tracking the frequencies and amplitudes of the sidebands around the fundamental frequency component with a very high accuracy. The efficiency of the proposed method is verified by simulation and experimental tests.

Experimental investigation on induction motors inter-turns short-circuit and broken rotor bars faults diagnosis through the discrete wavelet transform

This paper deals with the problem of fault detection in induction motors using the discrete wavelet transform (DWT) method. The DWT is a mathematical method used to extract different frequency components from a given signal. It is based on the decomposition of the processed signals into wavelet approximation and detail coefficients. In order to detect inter-turns short-circuit (ITSC) and broken rotor bars (BRBs) faults, the DWT is applied on two different signals: the current envelope and the current Park’s vector modulus. This study is performed using experimental tests carried-out on a 3 kW squirrel cage induction motor. The energy evaluation of known bandwidth details allows defining a fault severity factor (FSF). This FSF is used to show which signals, wavelet type and wavelet order are more sensitive for the fault detection task.ZusammenfassungDiese Arbeit befasst sich mit der Fehlererkennung in Asynchronmaschinen mittels diskreter Wavelet-Transformation (DWT). Die DWT ist eine mathematische Methode, um verschiedene Frequenzkomponenten aus einem gegebenen Signal zu extrahieren. Sie basiert auf der Zerlegung des verarbeiteten Signals in Tieffrequenzanteile und Hochfrequenzanteile. Um Windungsschlüsse und Rotorstabbrüche zu erkennen, wird die DWT auf zwei unterschiedliche Signale angewendet: die Hüllkurve des Stroms und den Betrag des Stromvektors nach der Park-Transformation. Die Untersuchungen wurden basierend auf Messungen an einer 3-kW-Asynchronmaschine mit Kurzschlussläufer durchgeführt. Die Auswertung der Leistungsanteile über den Frequenzbereich erlaubt die Definition eines Fehlerlevel-Faktors. Dieser Faktor kann verwendet werden, um für die Fehlererkennung geeignete Signale, Wavelet-Typen und Wavelet-Ordnungszahlen zu ermitteln.