Rotor Induction Machine Research Articles

Sliding Mode Control Restart Strategy for Rotating Induction Machine Using Time-Varying Switching Line

Sliding Mode Control Restart Strategy for Rotating Induction Machine Using Time-Varying Switching Line

Advanced Doubly Fed Induction Machine Rotor Fault Diagnosis Based on Wavelet Analysis in Closed-Loop Operation Under Time–varying Condition

This paper introduces a new diagnostic technique for the detection of incipient electrical rotor faults in doubly fed induction Machine (DFIM) for wind power systems. In the considered application, the rotor is supplied by a static converter for the control of active and reactive power flows from the generator to the electrical grid. A new diagnostic method based on the rotor modulating signals pre-processing by Frequency Sliding (FS) and Discrete Wavelet Transform (DWT) thereby is here proposed to detect rotor faults dynamically over time. Experimental and simulation results demonstrate the effectiveness of the proposed approach under time-varying conditions.

Use of Newton's Method for Rotor-Resistance Control of Wind Turbine Generators

The advancement in the use of renewable sources of electricity has been promoting the manufacture of wind turbines. This paper analyzes the influence of the insertion of resistance in the rotor of induction machines during voltage sags to improve its operation and presents a new approach. The control strategy uses the Newton’s Method, which is a numerical method. A simulation in a wind generator was realized, proving the control efficiency.

Fast Real-Time RDFT- and GDFT-Based Direct Fault Diagnosis of Induction Motor Drive

This paper presents the theoretical analysis and experimental verification of a direct fault harmonic identification approach in a converter-fed electric drive for automated diagnosis purposes. On the basis of the analytical model of the proposed real-time direct fault diagnosis, the fault-related harmonic component is calculated using recursive DFT (RDFT) and Goertzel DFT (GDFT), applied instead of the full spectrum calculations required in the most popular FFT algorithm. The simulation model of an inverter sensorlessly controlled induction motor drive is linked with the induction machine rotor fault model for testing the sensitivity of the GDFT- and RDFT-based fault diagnosis to state variable estimation errors. According to the presented simulation results, the accuracy of the direct identification of a fault-related harmonic is sensitive to the quality of fault harmonic frequency estimation. The sensitivity analysis with respect to RDFT and GDFT algorithms is included. Based on the experimental setup with a sensorlessly controlled induction motor drive with the investigated rotor fault, fault diagnosis algorithms were implemented in the microprocessor by integration with the control system in one microcontroller and experimentally verified. The RDFT and GDFT approach has shown accurate and fast direct automated fault identification at a significantly decreased number of arithmetical operations in the microcontroller, which is convenient for the frequency-domain fault diagnosis in electric drives and supports fault-tolerant control system implementation.

Recursive Singular Spectrum Analysis for Induction Machines Unbalanced Rotor Fault Diagnosis

One of the major challenges of diagnosing rotor symmetry faults in induction machines (IMs) is severe modulation of fault and supply frequency components. In particular, existing techniques are not able to identify fault components in the case of low slips. In this article, this problem is tackled by proposing a novel approach. First, a new use of singular spectrum analysis (SSA), as a powerful spectrum analyzer, is introduced for fault detection. Our idea is to treat the stator current signature of the wound rotor IM as a time series. In this approach, the current signature is decomposed into several eigenvalue spectra (rather than frequency spectra) to find a subspace where the fault component is recognizable. Subsequently, the fault component is detected using some data-driven filters constructed with the knowledge about characteristics of supply and fault components. Then, an inexpensive peak localization procedure is applied to the power spectrum of the fault component to identify the exact frequency of the fault. The fault detection and localization methods are then combined in a recursive regime to further improve the diagnosis’ performance particularly at high rotor speeds and small rotor faults. The proposed approach is data-driven and is directly applied to the raw signal with no suppression or filtration of the frequency harmonics with a low computational complexity. The numerical results obtained with real data at several rotation speeds and fault severities unveil the effectiveness and real-time feature of the proposed approach.

Rotor Temperature Virtual Sensing for Induction Machines Using a Lumped-Parameter Thermal Network and Dual Kalman Filtering

Accurate knowledge of the induction machine rotor temperature is important for both condition monitoring and motor performance. Lumped-parameter thermal networks allow to flexibly model the temperature distribution with low computational effort. However, their accuracy highly depends on the accuracy of their thermal parameters. Moreover, these parameters are determined offline and held constant during operation. In this article, a rotor temperature virtual sensing strategy is proposed, combining a lumped-parameter thermal network with stator windings temperature measurements. The latter measurement data can be easily collected and together with the thermal network serve as input to a dual Kalman filter to estimate both the rotor temperature evolutions and the thermal model parameters. The advantage of the presented approach is that the thermal model does not need exact identification for the considered motor. One can start from a thermal model identified from intrusive rotor measurement data on a comparable motor that is subsequently transferred to the motor to be monitored. This results in a fast and convenient way to estimate the rotor temperature in real-time. Experimental results on a 4-pole 5.5 kW induction machine demonstrate the validity of the presented strategy to accurately monitor the rotor temperature within an error range of approximately ±6 °C.

Elephant herding algorithm-based optimal PI controller for LVRT enhancement of wind energy conversion systems

This article introduces an optimal PI controller optimized by elephant herding algorithm (EHA) to control the grid-tied four-phase 8/6 switched reluctance generator (SRG). This controller is introduced for enhancing the low voltage ride through (LVRT) capability of the grid-tied SRG during faulty conditions that affect the SRG output voltage by regulating the off-delay angle of the generator. These faulty conditions include faults taken place at the point of connection (POC) of the SRG to the grid and wind speed variations. The proposed optimized PI controller regulates the off-delay angle of the generator to keep the voltage at the POC within acceptable limits. Maintaining these acceptable voltage limits during faulty conditions that keeps the generator in connection to the grid and makes the generator complying with the grid codes. Comparison between EHA optimization technique, cuckoo search optimization and particle swarm optimization (PSO) were presented to illustrate the effectiveness of the modern optimization technique used, EHA. An experimental verification of the proposed system is introduced by rewinding the stator and reshaping the rotor of three-phase induction machine to form four-phase, 8/6 SRG. Finite element method (FEM) based on ANSYS software is utilized to get the magnetic characteristics of the reconstructed 8/6 SRG after drawing the 3-D geometrical dimension in AUTOCAD.

A Restart Strategy of a Rotating Induction Machine for Inrush Current Elimination

In the application of electric railway traction, induction machines may suffer momentary power interruptions. Restarting control while machine running is a critical part of such applications, but residual flux in the free-running rotor deteriorates conventional controller performances, leading to inrush current and torque impact. Thus, this article proposes an improved feed-forward current controller that compensates voltage variations in the restart process. The residual rotor flux, as well as the induced back electromotive force, is estimated only with the measured speed in the free-running stage. The exact electromotive force is compensated at the restart moment, and the following current re-establishing stage. Based on the feed-forward compensation, the restart impact is eliminated and the restart current is controlled accurately in the predefined trajectories. Verified by experiments, the restart controller provides flexible restart manipulations.

Temporal envelope detection by the square root of the three-phase currents for IM rotor fault diagnosis

This paper deals with a reliable and effective method for induction machine rotor fault diagnosis, using three-phase stator currents. Through a theoretical demonstration based on the magnetic field approach, it has been shown that broken rotor bars produce amplitude modulation in the stator current which can be extracted with very low complexity by calculating the root of the squared three-phase stator currents. The theoretical background of the proposed method is presented then experimentally confirmed by using three currents measured from a test bench that contains three motors, one healthy and two other with broken bars. Each motor is subjected to two load conditions (low and high). The obtained results show the robustness and effectiveness of the proposed technique, even at low-load conditions, comparing to the classical MCSA method.

Key Assembling Issues Relating to Mechanical Vibration of Fabricated Rotor of Large Induction Machines

In many applications, where rotating machines of high power are used, high demands on reliability and safety are laid. Precise manufacturing procedures has to be kept even in case of machines retrofits when e.g. rotors are newly assembled. Even small inaccuracies or misguiding the precise technological procedure can lead to improper running of the machine and it can result in shut-down of complete drive. In case of primary circuits of nuclear power plants, it further means the shut-down of the whole power plant. Consequently, it results in significant financial losses (foregone profit and cost given by problem fixing). The paper presents a methodology of vibration origin investigation in case of large rotating machines which are part of drives like pump, compressors etc. The methodology is based on the detection of undesirable vibration using a diagnostic system on-site and further it uses mathematical modelling of corresponding mechanical parts to reveal the vibration origin. The modelling along with the measurement showed that the detected dangerous vibration is caused by misguided assembling of the rotor of the machine.

Computer‐aided analysis and design procedure for rotating induction machine magnetic circuits and windings

The aim of this study is to present a new, accurate, and user-friendly software procedure for the analysis and rapid design of rotating induction machine windings, considering both the electric and the magnetic specifications of the machine itself. This procedure is a valid aid for quick first stage design without the necessity of using finite element method (FEM)-based design procedures. FEM can be used in a second design phase in order to refine the first stage results. The design procedure is hereafter outlined and some examples show its capability.

Wireless Monitoring of Induction Machine Rotor Physical Variables.

With the widespread use of electric machines, there is a growing need to extract information from the machines to improve their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of the rotor physical variables of a squirrel cage induction motor. The system is comprised of: a circuit to acquire desirable rotor variable(s) and value(s) that send it to the computer; a rectifier and power storage circuit that converts an alternating current in a continuous current but also stores energy for a certain amount of time to wait for the motor’s shutdown; and a magnetic generator that harvests energy from the rotating field to power the circuits mentioned above. The embedded system is set on the rotor of a 5 HP squirrel cage induction motor, making it difficult to power the system because it is rotating. This problem can be solved with the construction of a magnetic generator device to avoid the need of using batteries or collector rings and will send data to the computer using a wireless NRF24L01 module. For the proposed system, initial validation tests were made using a temperature sensor (DS18b20), as this variable is known as the most important when identifying the need for maintenance and control systems. Few tests have shown promising results that, with further improvements, can prove the feasibility of using sensors in the rotor.

Induction Motor Rotor Bar Damage Evaluation With Magnetic Field Analysis

Detection of defects in induction machine rotor bars for disassembled motors are required to evaluate machines considered for repair as well as fulfilling incremental quality assurance checks in the manufacture of new machines. Detection of rotor bar defects prior to motor assembly are critical in increasing repair efficiency and assuring the quality of newly manufactured machines. Many methods of detecting rotor bar defects in unassembled motors lack the sensitivity to find both major and minor defects in both cast and fabricated rotors along with additional deficiencies in quantifiable test results and arc-flash safety hazards. A process of direct magnetic field analysis can examine measurements from induced currents in a rotor separated from its stator yielding a high-resolution fingerprint of a rotor's magnetic field. This process identifies both major and minor rotor bar defects in a repeatable and quantifiable manner appropriate for numerical evaluation without arc-flash safety hazards.

MRAS-based sensorless speed backstepping control for induction machine, using a flux sliding mode observer

In this paper, an induction machine rotor speed and rotor flux control using a sensorless backstepping control scheme is discussed. The most interesting point of this technique is that it deals with the nonlinearity of a high-order system by using the virtual control variable to make this system simple, and thus the control outputs can be derived step by step through appropriate Lyapunov functions. To avoid the use of a mechanical sensor, the rotor speed estimation is made by an observer using the model reference adaptive system (MRAS) technique; in order to estimate rotor flux, a sliding mode observer is proposed in this work. Simulation results are presented to validate and prove the effectiveness of the proposed sensorless control.

Descriptor-Type Kalman Filter and TLS EXIN Speed Estimate for Sensorless Control of a Linear Induction Motor

This paper proposes a speed observer for linear induction motors (LIMs), which is composed of two parts: 1) a linear Kalman filter (KF) for the online estimation of the inductor currents and induced part flux linkage components; and 2) a speed estimator based on the total least squares (TLS) EXIN neuron. The TLS estimator receives as inputs the state variables, estimated by the KF, and provides as output the LIM linear speed, which is fed back to the KF and the control system. The KF is based on the classic space-vector model of the rotating induction machine. The end effects of the LIMs have been considered an uncertainty treated by the KF. The TLS EXIN neuron has been used to compute, in recursive form, the machine linear speed online since it is the only neural network able to solve online, in a recursive form, a TLS problem. The proposed KF TLS speed estimator has been tested experimentally on a suitably developed test setup, and it has been compared with the classic extended KF.

Changing of Magnetic Flux Density Distribution in a Squirrel-Cage Induction Motor with Broken Rotor Bars

This paper presents the finite element modelling of three-phase squirrel-cage induction motor with broken rotor bar faults. Finite element model based on a real machine is constructed, propagation of broken rotor bar fault and its influence on the magnetic flux density distribution of the machine cage is observed. As the propagation of the fault will result in total breakdown of the induction machine rotor, if the fault is not detected and solved, necessity of condition monitoring is pointed out. Analysis of the fault and its affect to the magnetic field in the rotor cage as well as changes in the phase voltage spectrum are presented. DOI: http://dx.doi.org/10.5755/j01.eee.20.7.8018

Identification of harmful time harmonic interactions in a high power squirrel-cage traction machine

The paper offers a methodology for the identification the time harmonic interactions with a strong negative impact on the rotor of a high power induction machine. These potentially dangerous pulsating torques may be effectively reduced by carefully setting the machine’s drive control. A novel approach based on a complex finite element model and further post-processing is used. Results obtained from electromagnetic calculations in the form of pulsating torques are used as mechanical loading of a structural dynamic model. This complex model intended for rotor vibration analysis is described in brief in the mechanical part of the paper. The proposed methodology is applied to the machine used as a propulsion unit for multisystem locomotives of 1600kW power.

VALVE DIRECT CURRENT MOTOR ON THE BASIS OF THE SYNCHRONOUS MACHINE OF INVERSE DESIGN

A mechanical collector of conventional DC machine is the element that limits the current and the armature speed and increases inertia. DC machine rectification realized on the basis of conventional DC machine is described; it externally rectifies the switch which is the analogue of the collector. The armature has a design similar to a phase-wound rotor of induction machine. It is shown that the switching frequency is determined by the armature rotation speed. Static mechanical characteristic of the rectifying DC machine is similar to that of the independent excitation of DC motor. The proposed variant of the DC motor is actually a synchronous machine of inverse design with armature regulation frequency. The motor is described as traditional salient pole synchronous machine. Starting dynamics simulation shows that the rectifying DC machine has better dynamic properties compared to the conventional DC motor due to overload capability and reduces the inertia of the armature

A Novel Method for Excitation Control of DFIG Connected to the Grid on the Basis of Similar Signals from Rotor

This paper proposes a novel technique for the new excitation control of the doubly-fed induction generator (DFIG) on power-station which connected to the grid. That is using the similar signals from rotor of a small capacity doubly-fed induction machine (DFIM) as a base to generate the control signals for the former DFIG. Based on this method, a simple but effective controller is designed, which ensures to decouple the active and reactive power supplied to the grid by using two separate parameters Kp and Kq. The advantage of this method is that it is simple but still effective.

Reactive power allocation for loss minimisation in a stand alone variable speed constant frequency double output induction generator

Vector control algorithms reported so far for stand alone operation of variable speed constant frequency double output induction generators propose to supply the full magnetisation current of the machine in addition to the torque producing component from the rotor side converter. As the rotor of a normal induction machine is not designed for this additional load this approach leads to underutilisation of the machine torque capacity. Moreover, supplying the entire magnetisation current from the rotor side is not optimal from the point of view of the machine losses. Since the load voltage is regulated by manipulating the magnetising current through a slow acting flux control loop undesirable fluctuations in the load voltage waveforms are observed during fast load transients. An improved stator flux oriented control strategy for this type of generators, proposed in this study, eliminates undesirable load voltage transients by directly regulating the stator flux through the stator side converter. The total reactive power demand of the system is dynamically distributed between the two converters according to an optimum allocation program so as to minimise the losses without disturbing the stator flux. The effectiveness of the proposed algorithms is verified experimentally on a laboratory prototype.