Showing papers on "Induction motor published in 2008"

Models for Bearing Damage Detection in Induction Motors Using Stator Current Monitoring

Abstract: This paper describes a new analytical model for the influence of rolling-element bearing faults on induction motor stator current. Bearing problems are one major cause for drive failures. Their detection is possible by vibration monitoring of characteristic bearing frequencies. As it is possible to detect other machine faults by monitoring the stator current, a great interest exists in applying the same method for bearing fault detection. After a presentation of the existing fault model, a new detailed approach is proposed. It is based on the following two effects of a bearing fault: 1. the introduction of a particular radial rotor movement and 2. load torque variations caused by the bearing fault. The theoretical study results in new expressions for the stator current frequency content. Experimental tests with artificial and realistic bearing damage were conducted by measuring vibration, torque, and stator current. The obtained results by spectral analysis of the measured quantities validate the proposed theoretical approach.

Model Reference Adaptive Controller-Based Rotor Resistance and Speed Estimation Techniques for Vector Controlled Induction Motor Drive Utilizing Reactive Power

Abstract: In this paper, a detailed study on the model reference adaptive controller (MRAC) utilizing the reactive power is presented for the online estimation of rotor resistance to maintain proper flux orientation in an indirect vector controlled induction motor drive. Selection of reactive power as the functional candidate in the MRAC automatically makes the system immune to the variation of stator resistance. Moreover, the unique formation of the MRAC with the instantaneous and steady-state reactive power completely eliminates the requirement of any flux estimation in the process of computation. Thus, the method is less sensitive to integrator-related problems like drift and saturation (requiring no integration). This also makes the estimation at or near zero speed quite accurate. Adding flux estimators to the MRAC, a speed sensorless scheme is developed. Simulation and experimental results have been presented to confirm the effectiveness of the technique.

A Fuzzy-Based Approach for the Diagnosis of Fault Modes in a Voltage-Fed PWM Inverter Induction Motor Drive

Abstract: This paper investigates the use of fuzzy logic for fault detection and diagnosis in a pulsewidth modulation voltage source inverter (PWM-VSI) induction motor drive. The proposed fuzzy technique requires the measurement of the output inverter currents to detect intermittent loss of firing pulses in the inverter power switches. For diagnosis purposes, a localization domain made with seven patterns is built with the stator Concordia current vector. One is dedicated to the healthy domain and the six others to each inverter power switch. The fuzzy bases of the proposed technique are extracted from the current analysis of the fault modes in the PWM-VSI. Experimental results on a 1.5-kW induction motor drive are presented to demonstrate the effectiveness of the proposed fuzzy approach.

A General Approach for the Transient Detection of Slip-Dependent Fault Components Based on the Discrete Wavelet Transform

Abstract: In this paper, a general methodology based on the application of discrete wavelet transform (DWT) to the diagnosis of the cage motor condition using transient stator currents is exposed. The approach is based on the identification of characteristic patterns introduced by fault components in the wavelet signals obtained from the DWT of transient stator currents. These patterns enable a reliable detection of the corresponding fault as well as a clear interpretation of the physical phenomenon taking place in the machine. The proposed approach is applied to the detection of rotor asymmetries in two alternative ways, i.e., by using the startup current and by using the current during plugging stopping. Mixed eccentricities are also detected by means of the transient-based methodology. This paper shows how the evolution of other non-fault-related components such as the principal slot harmonic (PSH) can be extracted with the proposed technique. A compilation of experimental cases regarding the application of the methodology to the previous cases is presented. Guidelines for the easy application of the methodology by any user are also provided under a didactic perspective.

Induction Machine Broken Bar and Stator Short-Circuit Fault Diagnostics Based on Three-Phase Stator Current Envelopes

Abstract: A new method for the fault diagnosis of a broken rotor bar and interturn short circuits in induction machines (IMs) is presented. The method is based on the analysis of the three-phase stator current envelopes of IMs using reconstructed phase space transforms. The signatures of each type of fault are created from the three-phase current envelope of each fault. The resulting fault signatures for the new so-called ldquounseen signalsrdquo are classified using Gaussian mixture models and a Bayesian maximum likelihood classifier. The presented method yields a high degree of accuracy in fault identification as evidenced by the given experimental results, which validate this method.

Sensorless Control of Doubly-Fed Induction Generators Using a Rotor-Current-Based MRAS Observer

Abstract: This paper presents a new sensorless method for the vector control of doubly-fed induction machines (DFIMs) without using speed sensors or rotor position measurements. The proposed sensorless method is based on the model reference adaptive system (MRAS) estimating the rotor position and speed from the machine rotor currents. The method is appropriate for both stand-alone and grid-connected operation of variable speed DFIMs. To design the MRAS observer with the appropriate dynamic response, a small signal model is derived. The sensitivity of the method for variation in the machine parameters is also analyzed. Speed catching on the fly and synchronization of the doubly-fed induction generator with the utility are also addressed. Experimental results obtained from a 3.5-kW prototype are presented and fully analyzed.

Automatic Online Diagnosis Algorithm for Broken-Bar Detection on Induction Motors Based on Discrete Wavelet Transform for FPGA Implementation

Abstract: Overall system performance on a production line is one of the major concerns in modern industry where induction motors are present and their condition monitoring is mandatory. Periodic offline monitoring of the motor condition is usually performed in the industry, consuming production time and increasing cost. Broken rotor bars are among the most common failures in induction motors. Reported research projects give a broken-rotor-bar-detection methodology based on personal-computer implementation that is performed offline and requires an expert technician interpretation which is not a cost-effective solution. The novelty of this paper is the development of an automatic online diagnosis algorithm for broken-rotor-bar detection, optimized for single low-cost field-programmable gate-array (FPGA) implementation, which guarantees the development of economical self-operated equipment. The proposed algorithm requires less computation load than the previously reported algorithms, and it is mainly based on the discrete-wavelet-transform application to the start-up current transient; a further single mean-square computation determines a weighting function that, according to its value, clearly points the motor condition as either healthy or damaged. In order to validate the proposed algorithm, several tests were performed, and an FPGA implementation was developed to show the algorithm feasibility for automatic online diagnosis.

Five-Level Diode Clamped Inverter to EliminateCommon Mode Voltage and Reduce $dv/dt$ inMedium Voltage Rating Induction Motor Drives

Abstract: The High power induction machines are designed at medium voltage (MV) rating for better performance. The multilevel inverters (MLI) are able to provide medium voltage with high quality output at low switching frequency as compared to conventional two-level inverter. In addition to this, MLI reduces dv/dt, switching losses and leakage current. In this paper, approaches to reduce and eliminate the common mode voltage (CMV) using five- level diode clamped multilevel inverter (DCMLI) are presented. The CMV spikes are also eliminated by shifting dead-time across the phase pole. A novel technique for the selection of switching states to synthesize the desire vector is proposed. This paper realizes the implementation of five-level diode clamped MLI for three phase induction motor. Experimental results demonstrate the feasibility of the proposed solution.

A New PWM Strategy Based on a 24-Sector Vector Space Decomposition for a Six-Phase VSI-Fed Dual Stator Induction Motor

Abstract: This paper presents a new space vector pulsewidth modulation (SVPWM) technique for the control of a six-phase voltage source inverter (VSI)-fed dual stator induction machines (DSIM). A DSIM is an induction machine which has two sets of three-phase stator windings spatially shifted by 30 electrical degrees and fed by two three-phase VSIs. Despite their advantage of power segmentation, these machines are characterized by large zero sequence harmonic currents, and in particular those of order 6 k plusmn 1, which are due to the mutual cancellation between the two stator windings. The proposed SVPWM scheme, while easy to implement digitally, reduces significantly these extra stator harmonic currents. Experimental results, collected from a 15 kW prototype machine controlled by a digital signal processor, are presented and discussed.

Ride-Through Control of a Doubly Fed Induction Generator Under Unbalanced Voltage Sags

Abstract: This paper deals with the control of doubly fed induction generators to ride through unbalanced voltage sags. A control strategy is proposed by choosing certain current reference values in the positive and negative sequences so that the torque and the DC voltage are kept stable during such unbalanced sags. Both rotor- and grid-side converters are considered, detailing the control scheme of each converter while considering the effect of the crowbar protection. The control strategy is validated by means of simulations.

Predictive Current Control of an Induction Machine Fed by a Matrix Converter With Reactive Power Control

Abstract: A different approach to perform the control of an induction machine fed by a matrix converter (MC) is presented in this paper. The proposed technique is based on predictive control and effectively controls input and output variables to the power converter, as expected from an MC. The method allows the use of all valid switching states, including rotating vectors that are not considered in most control techniques, as space vector modulation or direct torque control for induction machines fed by MCs. Experimental results show the excellent performance of the proposed approach, with low-distortion input currents, adjustable power factor, sinusoidal output currents with smooth frequency transitions, and good speed control in motoring and regeneration conditions, even working under an unbalanced power supply. The implementation and comprehension of the method should be considered simple compared to other control strategies with similar features. The high computational effort required should not be a problem considering recent progresses in digital signal processors-and even less in years to come.

Effect of Zero-Vector Placement in a Dual-Inverter Fed Open-End Winding Induction-Motor Drive With a Decoupled Space-Vector PWM Strategy

Abstract: An open-end winding induction-motor drive with two two-level inverters achieves three-level inversion. The drawback of this configuration is the presence of a high zero-sequence current, stressing the semiconductor switching devices and the motor. To avoid this, two isolated dc power supplies are needed to feed individual inverters. In this paper, it is shown that it is possible to operate this drive with a single dc power supply, with reasonable engineering compromises. The new decoupled space-vector-based pulsewidth modulation (PWM) strategy proposed in this paper achieves this objective. This PWM strategy exploits the dependence of the zero-sequence voltage on the placement of the zero-vector of individual inverters. It is shown that the zero-sequence voltage of the dual-inverter system is suppressed by forcing the zero-sequence voltage of the individual inverters to a value of zero, in the average sense, in each sampling-time interval. This strategy, therefore, achieves a dynamic balancing of the zero-sequence current. It is also shown that this PWM scheme achieves the center spacing of effective-time period for the dual-inverter drive and its associated advantages. In addition, the effect of the placement of the zero-vector for individual inverters on the dual-inverter drive is investigated, and the experimental results are presented.

On-Line Monitoring of Mechanical Faults in Variable-Speed Induction Motor Drives Using the Wigner Distribution

Abstract: This paper deals with the detection of mechanical load faults in induction motors during speed transients. The detection strategy is based on stator current analysis. Mechanical load faults generally lead to load torque oscillations at specific frequencies related to the mechanical rotor speed. The torque oscillations produce a characteristic sinusoidal phase modulation of the stator current. Speed transients result in time-varying supply frequencies that prevent the use of classical, Fourier transform-based spectral estimation. This paper proposes the use of a time-frequency distribution, the Wigner Distribution, for stator current analysis. Fault indicators are extracted from the distribution for on-line condition monitoring. The proposed methods are implemented on a low-cost digital signal processor. Experimental results in a steady-state and during transients with load torque oscillations and load imbalance are presented.

An Effective Neural Approach for the Automatic Location of Stator Interturn Faults in Induction Motor

Abstract: This paper presents a neural approach to detect and locate automatically an interturn short-circuit fault in the stator windings of the induction machine. The fault detection and location are achieved by a feedforward multilayer-perceptron neural network (NN) trained by back propagation. The location process is based on monitoring the three-phase shifts between the line current and the phase voltage of the machine. The required data for training and testing the NN are experimentally generated from a three-phase induction motor with different interturn short-circuit faults. Simulation, as well as experimental, results are presented in this paper to demonstrate the effectiveness of the used method.

New Online Loss-Minimization-Based Control of an Induction Motor Drive

Abstract: This paper presents a new loss-model-based controller for an induction motor drive. Among the many loss minimization algorithms (LMA) for an induction motor, a loss-model-based approach has the advantages of fast response and high accuracy. However, the performance of the loss-model controller (LMC) depends on the accuracy of the modeling of the motor drive and losses. In the development of the loss model, there is always a tradeoff between accuracy and complexity. This paper presents a new LMC to determine an optimum flux level for the efficiency optimization of the vector-controlled induction motor drive. An induction motor (IM) model in d-q coordinates is referenced to the rotor magnetizing current. This transformation results in no leakage inductance on the rotor side, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the motor loss model. The suggested LMC is simple, but leakage inductances are not omitted. The complete closed loop vector control of the proposed LMC-based IM drive is successfully implemented in real-time using digital signal processor board DS 1104 for a laboratory 1/3 hp motor. The effectiveness of the proposed scheme is demonstrated through simulation and experimental results.

Experimental Evaluation of Braided EKF for Sensorless Control of Induction Motors

Abstract: Temperature- and frequency-dependent variations of the rotor (R'r) and stator (Rs) resistances pose a challenge in the accurate estimation of flux and velocity in the sensorless control of induction motors (IMs) over a wide speed range. Solutions have been sought to the problem by signal injection and/or by the use of different algorithms for the different parameters and states of the same motor. In this paper, a novel Extended-Kalman-Filter (EKF)-based estimation technique is developed for the solution of the problem based on the consecutive operation of two EKF algorithms at every time step. The proposed ldquobraidedrdquo EKF technique is experimentally tested under challenging parameter and load variations in a wide speed range, including low speed. The results demonstrate a significantly increased accuracy in the estimation of Rs and R'r, as well as load torque, flux, and velocity in transient and steady state, when compared with single EKFs or other approaches taken to estimate these parameters and states in the sensorless control of IMs. The improved results also motivate the utilization of the new estimation approach in combination with a variety of control methods which depend on accurate knowledge of a high number of parameters and states.

Selection of eLECTRIC mOTOR dRIVES for electric vehicles

Abstract: In this study, six kinds of the drivetrain systems of electric motor drives for EVs are discussed. Furthermore, the requirements of EVs on electric motor drives are presented. The comparative investigation on the efficiency, weight, cost, cooling, maximum speed, and fault-tolerance, safety, and reliability is carried out for switched reluctance motor, induction motor, permanent magnet blushless DC motor, and brushed DC motor drives, in order to find most appropriate electric motor drives for electric vehicle applications. The study shows that switched reluctance motor drives are the prior choice for electric vehicles.

Sensorless DTC-SVM for Induction Motor Driven by a Matrix Converter Using a Parameter Estimation Strategy

Abstract: This paper presents a new direct torque controlled space vector modulated method to improve the sensorless performance of matrix converter drives using a parameter estimation scheme. The flux and torque error are geometrically combined in a new flux leakage vector to make a stator command voltage vector in a deadbeat manner. A new sensorless method of estimating the rotor speed, flux, stator resistance, and rotor resistance is derived and verified with experimental results. Common terms in the error dynamics are utilized to find a simpler error model involving some auxiliary variables. Using this error model, the state estimation problem is converted into a parameter estimation problem assuming the rotor speed is constant. The proposed adaptive schemes are determined so that the whole system is stable in the sense of Lyapunov. The effectiveness of the proposed algorithm is verified by experiments.

Finite-Element Transient Analysis of Induction Motors Under Mixed Eccentricity Fault

Abstract: In a three-phase squirrel-cage induction motor, eccentricity is a common fault that can make it necessary to remove the motor from the production line. However, because the motor may be inaccessible, diagnosing the fault is not easy. We have developed a time-stepping finite-element method (FEM) that identifies mixed eccentricity (a combination of static and dynamic) by analysis, without direct access to the motor. The method overcomes the difficulty of applying FEMs to transient behavior. It simulates the spectrum of the line current of a production-line motor and compares it to the spectrum of a known healthy motor to detect eccentricity. Agreement between the simulation and actual measurements of eccentricity is good.Protection and fault diagnosis are integral to sound application of three-phase squirrel-cage induction motors in industry. Eccentricity is a common fault in induction motors that might force the motor to be removed from the production line. However, diagnosis of this fault due to inaccessibility to the rotor is not easy. Performance analysis, investigation and diagnosis of static, dynamic and mixed eccentricities at steady-state and during transient modes have already been published using analytical methods. However, study of static and dynamic eccentricities only at steady-state using finite element method (FEM) has been previously reported. This paper uses time stepping FE (TSFE) method with voltage-fed source for performance analysis and diagnosis of mixed eccentricity in induction motor at start up. The method used here overcomes the difficulty of FE application which makes it possible to analyze the transient behavior of a faulty induction motor. Spectra of line current of healthy motor and motor under mixed eccentricity conditions are predicted by simulation and then compared with the experimental results. This comparison shows a very good agreement between the simulation and test results.

Low Order PWM Inverter Harmonics Contributions to the Inverter-Fed Induction Machine Fault Diagnosis

Abstract: In this paper, the effects of inverter harmonics on motor current fault signatures are studied in detail. It is theoretically and experimentally shown that the fault signatures caused by the inverter harmonics are similar and comparable to those generated by the fundamental harmonic on the line current. Theoretically-derived extended relations including bearing fault, eccentricity, and broken rotor bar relations are found to match experimental results. Furthermore, it is observed and reported that the asymmetries on the rotor caused by broken rotor bars increase the amplitude of even harmonics. To confirm these claims, bearing, eccentricity, and broken rotor bar faults are tested and the line current spectrum of each faulty motor is compared with the healthy one. The proposed additional fault data are expected to contribute positively to the inverter-fed motor fault decision making algorithms.

Windings Temperature and Loss of Life of an Induction Machine Under Voltage Unbalance Combined With Over- or Undervoltages

Abstract: This paper deals with the effect of simultaneous voltage unbalance and over- or undervoltage on windings temperature and thermal loss of life of an induction cage machine. The presented results of investigations are based on the experiment and thermal modeling. The influence of an angle of the complex voltage unbalance factor (CVUF) on machine heating is considered. The effect of synergy of voltage unbalance and voltage rms value deviation is presented. Two induction machines of different properties are compared. One of them has a comparatively weakly saturated magnetic circuit, and the other a comparatively strongly saturated circuit. The former is especially exposed to overheating in the conditions of undervoltage, and the latter in the conditions of overvoltage.

Five-Level Diode-Clamped PWM Converters Connected Back-to-Back for Motor Drives

Abstract: This paper addresses a transformerless medium-voltage adjustable-speed motor drive consisting of two five-level diode-clamped PWM converters connected back-to-back. It is followed by designing, constructing, and testing a 200-V downscaled model to verify the validity and effectiveness of the medium-voltage motor drive. This downscaled model has four split DC capacitors equipped with a voltage-balancing circuit using two bidirectional buck-boost choppers. The two five-level converters are based on sinusoidal pulsewidth modulation with a carrier frequency of 3 kHz. The motor tested in this paper is a three-phase four-pole induction motor rated at 200 V, 5.5 kW, and 60 Hz. Experimental waveforms show that the four split dc-capacitor voltages are well balanced in any operating conditions and that the total harmonic distortion values of the input line current and the output motor current are 3.9% and 3.5%, respectively.

A Space Vector PWM Scheme for Multifrequency Output Voltage Generation With Multiphase Voltage-Source Inverters

Abstract: Multiphase variable-speed drives, supplied from two-level voltage-source inverters (VSIs), are nowadays considered for various industrial applications. Depending on the drive structure and/or the motor design, the VSI is required to generate either sinusoidal voltages or voltages that contain a certain number of sinusoidal components (ldquomultifrequency output voltagesrdquo). The existing space vector pulsewidth-modulation (SVPWM) schemes are based on selection of (n-1) active space vectors (for odd phase numbers) within a switching period and they yield either sinusoidal voltage or sinusoidal fundamental voltage in combination with a limited amount of other harmonic terms. This paper develops a SVPWM scheme, which enables multifrequency output voltage generation with arbitrary values of various sinusoidal components in the output voltage. The method is based on initial selection of (n-1)2/2 active space vectors within a switching period, instead of the common (n-1) active vectors. By properly arranging the sequence of the vector application, it is possible to provide an automatic postreduction of the number of applied active vectors to (n-1), thus maintaining the same switching frequency as with the existing schemes while simultaneously avoiding the limiting on the generated sinusoidal output voltage components. Theoretical considerations are detailed using a five-phase VSI. The experimental verification is provided using a five-phase two-motor series-connected induction motor drive, supplied from a custom-designed five-phase DSP-controlled VSI.

A Stochastic-Based FPGA Controller for an Induction Motor Drive With Integrated Neural Network Algorithms

Abstract: This paper applies stochastic theory to the design and implementation of field-oriented control of an induction motor drive using a single field-programmable gate array (FPGA) device and integrated neural network (NN) algorithms. Normally, NNs are characterized as heavily parallel calculation algorithms that employ enormous computational resources and are less useful for economical digital hardware implementations. A stochastic NN structure is proposed in this paper for an FPGA implementation of a feedforward NN to estimate the feedback signals in an induction motor drive. The stochastic arithmetic simplifies the computational elements of the NN and significantly reduces the number of logic gates required for the proposed NN estimator. A new stochastic proportional-integral speed controller is also developed with antiwindup functionality. Compared with conventional digital controls for motor drives, the proposed stochastic-based algorithm enhances the arithmetic operations of the FPGA, saves digital resources, and permits the NN algorithms and classical control algorithms to be easily interfaced and implemented on a single low-complexity, inexpensive FPGA. The algorithm has been realized using a single FPGA XC3S400 from Xilinx, Inc. A hardware-in-the-loop (HIL) test platform using a Real Time Digital Simulator is built in the laboratory. The HIL experimental results are provided to verify the proposed FPGA controller.

Combined Thermal and Electromagnetic Analysis of Permanent-Magnet and Induction Machines to Aid Calculation

Abstract: This paper reports on methods for the analysis of electrical machines by combined electromagnetic and thermal models using commercial software which can be an aid to the design of these machines. Examples using a brushless permanent-magnet motor and an induction motor illustrate the available tools and possible techniques. It reviews the different loss calculations, particularly iron losses, and also the thermal models that can be used, including steady state and transient (where thermal capacitances have to be included). This paper will be useful to an engineer in an industrial design office to illustrate the possibilities that are now possible.

Induction Motor Bearing Failure Detection and Diagnosis: Park and Concordia Transform Approaches Comparative Study

Abstract: This paper deals with the problem of bearing failure detection and diagnosis in induction motors. Indeed, bearing deterioration is now the main cause of induction motor rotor failures. In this context, two fault detection and diagnosis techniques, namely the Park transform approach and the Concordia transform, are briefly presented and compared. Experimental tests, on a 0.75 kW two-pole induction motor with artificial bearing damage, outline the main features of the aforementioned approaches for small- and medium-size induction motors bearing failure detection and/or diagnosis.

Comparative study of using different electric motors in the electric vehicles

Abstract: In this paper, different electric motors are studied and compared to see the benefits of each motor and the one that is more suitable to be used in the electric vehicle (EV) applications. There are five main electric motor types, DC, induction, permanent magnet synchronous, switched reluctance and brushless DC motors are studied. It is concluded that although the induction motors technology is more mature than others, for the EV applications the brushless DC and permanent magnet motors are more suitable than others. The use of these motors will result in less pollution, less fuel consumption and higher power to volume ratio. The reducing prices of the permanent magnet materials and the trend of increasing efficiency in the permanent magnet and brushless DC motors make them more and more attractive for the EV applications.

A Coupled Thermal–Electromagnetic Analysis for a Rapid and Accurate Prediction of IM Performance

Abstract: The design of electrical machines for extreme operating conditions must include a thermal analysis coupled with the magnetic analysis. However, the traditional coupling of the thermal and the magnetic models can result in an unacceptable increase in computation time, particularly if finite elements (FEs) are used for the machine analysis. This paper proposes a coupled thermal-magnetic analysis of an induction motor (IM) with the primary goal of achieving a rapid and accurate prediction of the IM performance. Only a minimum set of FE magnetic analyses is carried out so as to determine the parameters of the IM equivalent circuit. These parameters are nonlinear and are adjusted on the basis of the operating point. Then, this equivalent circuit is coupled with a lumped-parameter thermal network to predict the temperature in each part of the IM. Since both the equivalent circuit and thermal network solutions are analytic, the analysis converges very rapidly. At the same time, the FE analysis yields a precise estimation of the IM parameters used in the equivalent circuit. Some experimental results are reported, showing the accurate prediction of the proposed methodology.

A Predictive Algorithm for Controlling Speed and Rotor Flux of Induction Motor

Abstract: A model-based predictive control of rotor flux and speed of a vector-controlled induction motor (IM) is presented. A state-space approach is employed for modeling a rotor-flux-oriented IM. The control law is derived by optimization of an objective function that considers the control effort and the difference between the predicted outputs (speed and rotor flux) and the specific references, with predicted outputs calculated using a linearized state-space model. The rotor flux and speed are estimated by using an extended Kalman filter. In this model, the load inertia is unknown, and the external load torque is considered to be a disturbance. Its amplitude is computed with the electromechanical equation or estimated by the Kalman filter. Simulated and experimental results show the good performance of this strategy.