Three-phase Squirrel-cage Induction Machine Research Articles

Detection of Broken Rotor Bars in a Cage Induction Machine Using DC Injection Braking

In this paper, an effective procedure for broken rotor bar (BRB) fault detection in a three-phase squirrel-cage induction machine (SCIM) is proposed. This approach relies on a motor current signature analysis (MCSA) by observing the specific fault-related current component generated by applying the DC injection braking method. Unlike the traditional MCSA, which is commonly focused on the detection of BRB sidebands around the fundamental current component, the proposed methodology introduces a new BRB feature in the current spectrum which makes it much easier for identification. The distinctive time-frequency evolution pattern of this feature provides the reliable identification of BRBs, even under no-load operating conditions, thus overcoming the major drawback of traditional MCSA-based methods. Fault severity classification is easily performed through the magnitude inspection of the BRB fault-related current component. In addition, the proposed approach does not require high-complexity signal processing algorithms to achieve reliable results. The proposed concept is presented theoretically, assisted by a magnetically coupled multiple circuit model of the SCIM, both with healthy and faulty rotor bars. Finally, the experimental tests validate the proposed methodology and demonstrate its effectiveness and usefulness.

Space Harmonics and Saturation Interaction in Fault-Tolerant Induction Machine Drives Due to a Zero-Sequence Stator Current

Postfault operation strategies for three-phase squirrel cage induction machine drives enable increased fault-tolerance in the case of inverter faults. However, in strategies that apply a zero-sequence stator current, additional space harmonics interact with the fundamental wave. This article studies these space harmonics and the occurring saturation interaction with the main system based on two different induction machines. For illustration, and to support the analysis with quantitative results, it exemplarily investigates the effects of this saturation interaction on the flux linkages and the torque during the postfault operation of a rotor flux-oriented drive.

Analysis of Transient Magnetic Force on End-Winding in the Inverter-Fed Induction Machine

The increasing harmonics caused by inverter supply have an adverse impact on the end-winding vibration of the induction machine in accelerating failure and adding noise. Therefore, this paper puts forward an approach for end-winding magnetic force calculation in the inverter-fed induction machine. The 2D field–circuit–motion coupling analysis is used to calculate the stator currents in an induction machine, which are taken as loads in 3D transient magnetic analysis to obtain magnetic force on the end-windings. A three-phase squirrel-cage induction machine was designed and an experiment was carried out on the test motor to validate the proposed model. The simulated stator current, magnetic flux density and magnetic force agree well with both the theoretical analysis and measured results. Finally, a 3-D transient structural simulation was performed to further analyze the end-winding vibration. However, there is some difference of end-winding vibration acceleration between the simulation and experiment in harmonic components. The above deviation is probably attributed to the structure simplification of the induction machine. Thus, the developed simulation model can calculate the magnetic force on end-winding with reasonable accuracy, but it is advisable to perform an experimental study to fully analyze the vibration characteristics of end-winding.

Analysis of the Impact of Stator Interturn Short-Circuit Faults on Induction Machines Driven by Direct Torque Control

This paper addresses the analysis of three-phase squirrel-cage induction machine (IM) with interturn short-circuit (ITSC) fault and its influence on direct torque control (DTC). The particularities of the DTC such as its behavior, its standard heuristic derivation, and its nature of been a nonlinear hysteresis-based predictive controller are exploited, thus allowing the improvement and development of alternative explanations to the phenomena. The understanding of DTC and the development of the current state–space model of the asymmetric IM, presented here for first time in the literature, enables the analytical treatment of the research topic and the discovery of several DTC reactions to the fault. The ITSC impact on DTC and its reaction leads to the following twofold characterizations: first, unobservable and visible effects, and second, compensation and tolerant reactions. For purposes of simulation, a plug-and-play configurable circuit-block for the asymmetric IM was developed based on Norton's equivalent circuit. Simulation and experimental results demonstrate the assertiveness of the developed analyses and theoretical findings, which allows future research in online fault diagnostics and condition monitoring of inverter-fed IM with this type of fault.

Induction machine fault detection using smartphone recorded audible noise

This study presents induction machine fault detection possibilities using smartphone recorded audible noise. Acoustic and audible noise analysis for fault detection is a well-established technique; however, specialised equipment for diagnostic purposes is often very expensive and difficult to operate. To overcome this obstacle, a simple pre-diagnostic procedure, using hand-held smartphones is proposed. Different faults of the three-phase squirrel cage induction machine such as various numbers of broken rotor bars and dynamic rotor eccentricity are inflicted to the machine and the resulting audible signals are recorded in laboratory circumstances using two widely available commercial smartphones. The analysis is performed on audible noise and compared with the results of mechanical vibrations measurements, recorded by vibration sensors. Rotational speed frequency and twice-line frequency are used as diagnostic indicators of faults. A simple neural network is composed and probabilities of fault detection using such diagnostic measures are presented. The necessity for further study as well as further implementation and method refinement necessity is pointed out.

A Hierarchical Approach for the Recognition of Induction Machine Failures

Due to its sturdiness, low cost and ease of implementation, the induction machine is one of the most common electrical motors used in industry. However, this machine still concedes failures leading to unplanned shutdowns, sources of significant financial losses. For this reason, induction machine failure diagnosis has become an ordinary task, where some ameliorations have to be achieved in order to improve the efficiency of maintenance programs by minimizing the number and the time period of unexpected shutdowns. In this paper, we address the recognition of inter-turn short circuit (ITSC) in the stator windings and broken rotor bars (BRBs) in the three-phase squirrel cage induction machine by proposing a new approach. This approach relies on the three-phase current analysis method to extract features and a new hierarchical recognition algorithm based on an ensemble of three different classifiers. In addition, the present work studies the failures recognition of the induction machine operating with a torque and speed control. The proposed approach is a major advanced for the induction machine diagnosis research because it recognizes correctly (detects, localizes and estimates the degree of severity) ITSC and (detects and estimates) BRB faults with an accuracy of 93.36% and with a great robustness compared to a classical machine learning algorithm.

The deterministic bispectrum of coupled harmonic random signals and its application to rotor faults diagnosis considering noise immunity

This paper considers the properties of a bispectrum estimate when applied to a system with quadratic nonlinearity excited by the superposition of harmonics in the presence of additive Gaussian noise. This is compared using signal-to-noise ratios, to the power spectrum. Numerical examples were included to verify the results. In addition, an application of the use of the bispectrum to detect rotor faults in rotating machinery through detection of quadratic phase coupling is presented. The paper aims to clarify the use of the bispectrum to detect non-linearity in time series and presents the background theory on the bispectrum and in its application. Further, we show how patterns in the bispectrum are useful for identifying the frequency (or bifrequency) components involved in the non-linear interaction. The properties of interest are insensitivity to Gaussian noise and it’s ability to detect quadratic phase coupling. The study aims to expand the domain of induction machines faults diagnosis. To verify the theoretical development, stator currents which were collected from a test bed based on a 18.5kW three-phase squirrel cage induction machine have been used in a steady-state condition.

Fault Index Statistical Study for Gear Fault Detection Using Stator Current Space Vector Analysis

This paper presents a statistical analysis on a fault index computed based on the stator current space vector instantaneous frequency on a real-time platform for online noninvasive gear tooth surface damage fault detection in a single-stage gearbox. This analysis is crucial for defining a threshold beyond which the condition of gear teeth can be considered defective with a significance level less than the critical value. Besides, the efficiency of the fault detection algorithm realized on a real-time platform will be evaluated for both pinion and wheel tooth surface damage faults by using a setup based on a 250-W three-phase squirrel-cage induction machine shaft-connected to a single-stage spur or helical gearboxes.

Variable‐speed wind energy conversion system based on a dual stator‐winding induction generator

This study presents a wind energy conversion system based on a dual stator-winding induction generator. The generator can work at variable wind speed and can also be connected to the grid. The proposed energy conversion system presents three operation zones that depend on the wind speed and are delimited by the power ratio assigned to each of the two stator windings. The generator design starts from a three-phase squirrel-cage induction machine and allows a simple assembling of the new windings, what results in an economical, robust and reliable machine. These features make the generator appropriate for wind energy conversion systems located in remote places or in developing areas with limited resources, as well as for distributed generation systems and microgrids. This report also includes experimental and simulation results of the generator operation in the three working areas.

Speed control of sensorless induction generator by artificial neural network in wind energy conversion system

This study presents a new strategy for estimating the states (rotor flux and speed) and the load torque to implement a multivariable controller for a sensorless three-phase squirrel-cage induction machine in wind energy conversion systems. The multivariable control is carried out using input–output feedback law and its objective is to track profiles of the rotational speed and the rotor flux amplitude. The state estimation considerably improves the performance of rotor flux based model reference adaptive system in the variable speed region of operation. The technique uses Kalman filter as a rotor flux observer and an artificial neural network adaption mechanism to estimate the rotor speed. The state estimation requires only the measurements of the stator voltages and currents. The estimation method, for both states and torque, is not invasive as no mechanical sensors are needed. The wind energy conversion system and the proposed control-estimation techniques are simulated in Matlab/Simulink software platform and tested using the OPAL-RT real-time simulator (OP5600) to verify the accuracy of the proposed control-estimation method.

Inductances Evaluation of a Squirrel-Cage Induction Motor with Curved Dynamic Eccentricity

Eccentricity faults more or less exist in all rotating electrical machines. This paper establishes a more precise model of dynamic eccentricity (DE) in electrical machines named as curved dynamic eccentricity. It is a kind of axial unequal eccentricity which has not been investigated in detail so far but occurs in large electrical machines. The inductances of a large three-phase squirrel-cage induction machine (SCIM) under different levels of curved DE conditions are evaluated using winding function approach (WFA). These inductances include the stator self and mutual inductances, rotor self and mutual inductances, and mutual inductances between stator phases and rotor loops. A comparison is made between the calculation results under curved DE and the corresponding pure DE conditions. It indicates that the eccentricity condition will be more terrible than the monitored eccentricity based on the conventional pure DE model.

Multi-Objective Optimal Design of a NEMA Design D Three-phase Induction Machine Utilizing Gaussian-MOPSO Algorithm

This paper presents a multi-objective optimization approach to design rotor slot geometry of three-phase squirrel cage induction machine to achieve NEMA design D torque-speed (T-S) characteristics with high efficiency. The multi-objective Particle Swarm Optimization (MOPSO) algorithm combined with the adaptive response surface method and Latin hypercube sampling strategy is applied to obtain the Pareto optimal designs. In order to demonstrate the validity of the suggested optimal algorithm, an application to rotor slot design of three-phase induction motor is presented.

A MODIFIED MODEL OF SQUIRREL CAGE INDUCTION MACHINE UNDER GENERAL ROTOR MISALIGNMENT FAULT

A great deal of researches have so far been conducted on the analysis of eccentricity in induction machines. However, they mostly consider radial non-uniformity and neglect non-uniformity in the axial direction, but in practice, the axial non-uniformity due to rotor misalignment faults is quite common. This paper presents a modifled model of a three-phase squirrel cage induction machine under difierent rotor misalignment conditions. For this purpose, general expressions for air gap and mean radius of induction machine, considering axial non-uniformity, have been developed. The proposed model is able to calculate the time varying inductances versus rotor angle for three-phase squirrel cage induction machines under general rotor misalignment, including static, dynamic and mixed rotor misalignment in the frame of a single program. Simulation results were verifled by the experimental ones. The model presented by Tolyiat et al. (1) has been shown to be accurate for the time domain simulation of AC motors based on the basic geometry and winding layout of stator windings and rotor loops. Contrary to the classical d-q model, this theory can take into account all of the winding magnetomotive force space harmonics. An essential part of this theory is the calculation of machine inductances. These inductances are calculated using winding function and other equations within the theory. By this approach, all space harmonics are taken into account without any restriction concerning symmetry of stator or rotor windings. Hence, this model is widely used for the analysis of

Performance Analysis of Induction Machines with Unconventional Winding Configurations

This paper presents the performance of fractional slots distributed windings (FSDW) and fractional slots concentrated windings (FSCW) of three-phase squirrel cage induction machines. The different windings have been designed and modeled using the same machine physical and electrical parameters. The Finite Element Model (FEM) of the machine for the different windings has been carried out. The results for the machine with FSDW and FSCW are compared to the results of the conventional double layer (CDL) with 8/9 chorded coil.

Wire Rope Fault Detection in a Hoisting Winch System by Motor Torque and Current Signature Analysis

The aim of this paper is to analyze theoretically and experimentally the stator current and load torque of a three-phase induction machine in a hoisting winch system. This is performed in order to show how these variables are influenced by the wire rope faulty conditions. When the wire rope is subject to axial and torsional loads, the outer strands can be separated from the core in a permanent way and make the rope less reliable. The term “birdcaging” is used to describe this type of phenomenon by giving a permanent appearance of a wire rope forced into compression. In a hoisting winch system, the rope is bent over a drum and a pulley, and it is torsionally stressed by the fleet angle between them. In this paper, the effect of the fleet angle is observed in the stator current and the load torque in order to detect the “birdcaging” effect. This study is performed on a 22-kW three-phase squirrel-cage induction machine driving a reduced scale winch system, and it presents an original noninvasive way to detect a wire rope fault condition.

Digital Signal Processor-based Controller Design and Implementation for Self-excited Induction Generator

This article presents the design and implementation of a digital signal processor (DSP)-based induction generator controller (IGC) to regulate the voltage and frequency of a single-phase self-excited induction generator (SEIG), which employs a three-phase squirrel-cage induction machine that is suitable for the stand-alone power mode and employing an unregulated turbine, such as micro-hydro power generation. A three-phase induction machine can be used to generate single-phase supply at constant voltage and frequency if the electrical load is constantly maintained at its terminals. A prototype model of a single-phase SEIG is developed, such that the load on the SEIG remains constant despite a change in the consumer load. The transient behavior of the developed DSP-based SEIG–IGC system at different operating conditions, such as application and removal of static (resistive and reactive) and dynamic (single-phase induction motor) load, is investigated to demonstrate the capabilities of the proposed IGC.

A High-Resolution Frequency Estimation Method for Three-Phase Induction Machine Fault Detection

Fault detection in alternating-current electrical machines that is based on frequency analysis of stator current has been the interest of many researchers. Several frequency estimation techniques have been developed and are used to help the induction machine fault detection and diagnosis. This paper presents a technique to improve the fault detection technique by using the classical multiple signal classification (MUSIC) method. This method is a powerful tool that extracts meaningful frequencies from the signal, and it has been widely used in different areas, which include electrical machines. In the proposed application, the fault sensitive frequencies have to be found in the stator current signature. They are numerous in a given frequency range, and they are affected by the signal-to-noise ratio. Then, the MUSIC method takes a long computation time to find many frequencies by increasing the dimension of the autocorrelation matrix. To solve this problem, an algorithm that is based on zooming in a specific frequency range is proposed with MUSIC in order to improve the performances of frequency extraction. Moreover, the method is integrated as a part of MUSIC to estimate the frequency signal dimension order based on classification of autocorrelation matrix eigenvalues. The proposed algorithm has been applied to detect a rotor broken bar fault in a three-phase squirrel-cage induction machine under different loads and in steady-state condition.

Analytical Approach of the Stator Current Frequency Harmonics Computation for Detection of Induction Machine Rotor Faults

The aim of this paper is to analyze theoretically and experimentally the stator current of a three-phase squirrel-cage induction machine in order to show how it is influenced by electrical rotor faults. The approach used for this study analyzes the modification introduced by n broken rotor bars in the rotor cage magnetomotive force and then estimates the resulting frequency spectrum in the stator current. This approach is validated in a 3-kW 230-V/400-V 50-Hz 2850-r/min two-pole three-phase induction machine, showing the sensitive frequency components to rotor fault condition.

Detection of Induction Machines Rotor Faults at Standstill Using Signals Injection

The main topic of this paper is to examine the feasibility of detecting the rotor faults of induction machines by performing standstill tests. It has been shown that by feeding the machine with special excitation signals such as discrete interval binary sequence (DIBS) and multisine, it is possible to excite with low-frequency resolution the faulty modes by analyzing the stator current and the stray flux measured by an external flux sensor. This method can be used for quality control just after manufacturing the rotor and mounting it within the stator frame. The proposed technique is fully general and can be applied to a three-phase squirrel-cage induction machine at standstill. Experimental measurements are made both on healthy and faulty machines and the comparison gives a difference in the external flux and stator current signatures which are basically the most commonly used methods for rotor fault detection.

An Equivalent Internal Circuit of the Induction Machine for Advanced Spectral Analysis

The aim of this paper is to develop a method to validate an equivalent internal circuit of the three-phase squirrel-cage induction machine for advanced signal processing including fault diagnosis. The proposed method is based on the computation of the stator and rotor current spectra. An experimental setup for an 11-kW induction machine was developed in order to get numerical data for voltages and currents from the stator side. The comparison between the analytical computation, the simulation, and the experimental results, shows the model capability to reproduce the electromagnetic phenomena in the induction machine with mixed time and space harmonics. The proposed model can be used to design electrical fault detection devices with low cost and noninvasive sensors.