Rotor fault analysis in a doubly-fed induction generator using impedance matrix technique

© 2017 IEEE. Condition monitoring is a standard method for scheduling maintenance and ensuring that catastrophic failures do not occur in industrial motors

Predicting the behavior of induction machine using motor-CAD and MATLAB packages

© 2018 IEEE. Design optimization of induction machines uses computer aided design. These machines are the most suitable choice for various and complex industrial applications and improved efficiency is a key point. Wound rotor induction machines have enjoyed a renascence as the generator in many commercial wind turbines. In this paper, both Motor-CAD and MATLAB packages are employed to predict the electromagnetic behavior of an induction machine during steady-state and transient-state. Finite element analysis of a three-phase, four-pole induction machine is carried by using Motor-CAD and MATLAB in order to complete the comparison. The graphical interfaces of Motor-CAD environment will be utilized to describe the machine geometry, winding harmonics, material properties, and air-gap flux. The predicted results are validated by the experiment. Power losses are calculated for the test machine, and then the results will be explained

On the identifiability, parameter identification and fault diagnosis of induction machines

PhD ThesisDue to their reliability and low cost, induction machines have been widely utilized in a large variety of industrial applications. Although these machines are rugged and reliable, they are subjected to various stresses that might result in some unavoidable parameter changes and modes of failures. A common practice in induction machine parameter identification and fault diagnosis techniques is to employ a machine model and use the external measurements of voltage, current, speed, and/or torque in model solution. With this approach, it might be possible to get an infinite number of mathematical solutions representing the machine parameters, depending on the employed machine model. It is therefore crucial to investigate such possibility of obtaining incorrect parameter sets, i.e. to test the identifiability of the model before being used for parameter identification and fault diagnosis purposes. This project focuses on the identifiability of induction machine models and their use in parameter identification and fault diagnosis. Two commonly used steady-states induction machine models namely T-model and inverse Γ- model have been considered in this thesis. The classical transfer function and bond graph identifiability analysis approaches, which have been previously employed for the T-model, are applied in this thesis to investigate the identifiability of the inverse Γ-model. A novel algorithm, the Alternating Conditional Expectation, is employed here for the first time to study the identifiability of both the T- and inverse Γ-models of the induction machine. The results obtained from the proposed algorithm show that the parameters of the commonly utilised Tmodel are non-identifiable while those of the inverse Γ-model are uniquely identifiable when using external measurements. The identifiability analysis results are experimentally verified by the particle swarm optimization and Levenberg-Marquardt model-based parameter identification approaches developed in this thesis. To overcome the non-identifiability problem of the T-model, a new technique for induction machine parameter estimation from external measurements based on a combination of the induction machine’s T- and inverse Γ-models is proposed. Results for both supply-fed and inverter-fed operations show the success of the technique in identifying the parameters of the machine using only readily available measurements of steady-state machine current, voltage and speed, without the need for extra hardware. ii A diagnosis scheme to detect stator winding faults in induction machines is also proposed in this thesis. The scheme uses time domain features derived from 3-phase stator currents in conjunction with particle swarm optimization algorithm to check characteristic parameters of the machine and detect the fault accordingly. The validity and effectiveness of the proposed technique has been evaluated for different common faults including interturn short-circuit, stator winding asymmetry (increased resistance in one or more stator phases) and combined faults, i.e. a mixture of stator winding asymmetry and interturn short-circuit. Results show the accuracy of the proposed technique and it is ability to detect the presence of the fault and provide information about its type and location. Extensive simulations using Matlab/SIMULINK and experimental tests have been carried out to verify the identifiability analysis and show the effectiveness of the proposed parameter identification and fault diagnoses schemes. The constructed test rig includes a 1.1 kW threephase test induction machine coupled to a dynamometer loading unit and driven by a variable frequency inverter that allows operation at different speeds. All the experiment analyses provided in the thesis are based on terminal voltages, stator currents and rotor speed that are usually measured and used in machine control.Libya, through the Engineering Faculty of Misurata- Misurata Universit

Condition monitoring of wound-rotor induction machines

University of Technology Sydney. Faculty of Engineering and Information Technology.Condition monitoring enables diagnosis of the inception of fault mechanisms in electrical machines, thus averting failure and the need of expensive repairs. Therefore, it is valuable to develop efficient methods of condition monitoring. The idea would be relatively low cost and/or non-invasive system, which is still sufficiently powerful in terms of monitoring by online detection of developing faults. In this research, an overview of existing condition monitoring techniques is given, and issues related to induction machine faults are discussed. Therefore, this research develops a relatively simple yet powerful model for studying the behaviour of a wound rotor induction machine (WRIM) or doubly fed induction generator (DFIG) in healthy and faulty conditions based on the impedance matrix. The first part of the work presented in this dissertation builds the fundamental impedance matrix that can predict the behaviour of the WRIM or DFIG in a healthy condition. A theoretical model is necessary so that any stator or rotor winding configuration in the machine can be incorporated. The effect of rotor skew is considered in this model. Then, the Motor-CAD package is employed to predict the electromagnetic behaviour of the induction machine during steady-state and transient-state operation. Motor-CAD has been used for examining the induction machine parameters. The second part of the work develops the impedance matrix to detect unbalanced rotor-phase impedances. This can simulate rotor faults in the machine. The method leads to the calculation of stator current components when there are unbalanced rotor-phase impedances and it is verified experimentally using a four-pole wound rotor. The method is verified by inversion of the voltage matrix equation and solving for the currents in the wound motor. Experimental results (torque and current characteristic) are compared with computer predictions for the test machine. The third part of this thesis develops the fundamental impedance matrices for both rotor eccentricity detection and unbalanced magnetic pull (UMP) calculation. It puts forward a concept for detecting and measuring eccentricity faults in the WRIM. A simple and new approach using pole-specific search coils is introduced, and a theory is developed to illustrate that rotor eccentricity leads to the generation of air-gap flux waves with pole-pairs of p ± 1, where p is the number of pole-pairs of the machine. Once again, this technique is used here to detect rotor eccentricity in a four-pole wound rotor machine and is verified experimentally using a rig for measuring UMP. The investigation uncovers several aspects of the damping effects of pole-specific search windings which can also be used to suppress UMP

The monitoring of induction motor starting transients with a view to early fault detection.

The aim of this work is to investigate the possibility of detecting faults in a 3 phase Induction motor by monitoring and analysing the transient line current waveform during the starting period. This is a particularly onerous time for the machine and the inter-relationships between parameters such as current, torque, speed and time are very complex. As a result two parallel paths of investigation have been followed, by methods of experimentation and computer simulation. Transient line current signals have been obtained from purpose built test rigs and these signals have been analysed in both the time and frequency domains. In order to assist with the comprehension of this data a sophisticated computer simulation of the induction motor during the starting period has also been developed. Computer simulation of the induction motor has been developed initially using the two and then three phase induction motor voltage equations which are solved by numerical integration. Using these techniques it has been possible to detect small degrees of fault level for both wound and cage rotor machines by analysing the line current waveform during the starting period. Good agreement has been found between the real and simulated data. A range of Digital Signal Processing techniques have been utilised to extract the components indicative of rotor faults. These techniques were at first wideband and highly numerically intensive, some originating from Speech Processing. The final processing techniques were far simpler and selected by analysis of the results from experimental data, both real and simulated

Advances in Electrical Machine, Power Electronic, and Drive Condition Monitoring and Fault Detection: State of the Art

© 2015 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] Recently, research concerning electrical machines and drives condition monitoring and fault diagnosis has experienced extraordinarily dynamic activity. The increasing importance of these energy conversion devices and their widespread use in uncountable applications have motivated significant research efforts. This paper presents an analysis of the state of the art in this field. The analyzed contributions were published in most relevant journals and magazines or presented in either specific conferences in the area or more broadly scoped events.Riera-Guasp, M.; Antonino-Daviu, J.; Capolino, G. (2015). Advances in Electrical Machine, Power Electronic, and Drive Condition Monitoring and Fault Detection: State of the Art. IEEE Transactions on Industrial Electronics. 62(3):1746-1759. doi:10.1109/TIE.2014.2375853S1746175962

Multiphase induction motor drives - a technology status review

The area of multiphase variable-speed motor drives in general and multiphase induction motor drives in particular has experienced a substantial growth since the beginning of this century. Research has been conducted worldwide and numerous interesting developments have been reported in the literature. An attempt is made to provide a detailed overview of the current state-of-the-art in this area. The elaborated aspects include advantages of multiphase induction machines, modelling of multiphase induction machines, basic vector control and direct torque control schemes and PWM control of multiphase voltage source inverters. The authors also provide a detailed survey of the control strategies for five-phase and asymmetrical six-phase induction motor drives, as well as an overview of the approaches to the design of fault tolerant strategies for post-fault drive operation, and a discussion of multiphase multi-motor drives with single inverter supply. Experimental results, collected from various multiphase induction motor drive laboratory rigs, are also included to facilitate the understanding of the drive operatio

Experimental Investigation Of On-Line Methods For Incipient Fault Detection

Condition-based maintenance (CBM) of industrial equipment is generally recognized as being the most cost-effective means for improving equipment availability. However, prerequisite to successful implementation of CBM is a reliable detector of failing components. One such detector, termed the effective negative-sequence impedance, had previously been identified as an indicator of induction motor stator winding degradation. However, a limitation of this detector is that it does not change in a predicable manner under certain motor operating conditions. This paper presents an experimental investigation of an improved technique for on-line detection of induction motor stator winding degradation. The paper begins with a brief description of the detectors, followed by a detailed description of the experimental setup, the experiments conducted, and results.2000845

Online monitoring of turn insulation deterioration in mains-fed induction machines using online surge testing

The development of an online method for the early detection of a stator turn insulation deterioration is the objective of the research at hand. A high percentage of motor breakdowns is related to the failure of the stator insulation system. Since most of the stator insulation failures originate in the breakdown of the turn-to-turn insulation, the research in this realm is of great significance. Despite the progress that has been made in the field of stator turn fault detection methods, the most popular and the best known ones are still limited to the detection of solid turn faults. The time span between a solid turn fault and the breakdown of the primary insulation system can be as short as a few seconds. Therefore, it is desirable to develop a method capable of detecting the deterioration of the turn insulation as early as possible and prior to the development of a solid turn fault. The different stresses that cause the aging of the insulation and eventually lead to failure are described as well as the various patterns of an insulation failure. A comprehensive literature survey shows the methods presently used for the monitoring of the turn insulation. Up to now no well-tested and reliable online method that can find the deterioration of the turn insulation is available. The most commonly used turn insulation test is the surge test, which, however, is performed only when the motor is out of service and disconnected from the supply. So far no research at all has been conducted on the application of an online surge test. The research at hand examines the applicability of the surge test to an operating machine. Various topologies of online surge testing are examined with regard to their practicability and their limitations. The most practical configuration is chosen for further analysis, implementation and development. Moreover, practical challenges are presented by the non-idealities of the induction machine like the eccentricity of the rotor and the rotor slotting, and have to be taken into account. Two solutions to eliminate the influence of the rotor position on the surge waveform are presented. Even though the basic concepts of online surge testing can be validated experimentally by a machine with a solid turn fault, it is preferable to use a machine with a deteriorated turn insulation. Therefore, a method, which does not require complex and expensive hardware, to experimentally emulate the turn insulation breakdown is implemented. The concepts at any stage of the work are supported by simulations and experimental results. In addition, the theory of surge testing is further developed by giving new definitions of the test's sensitivity, i.e., the frequency sensitivity and the error area ratio (EAR) sensitivity.Ph.D.Committee Chair: Thomas G. Habetler; Committee Member: Deepakraj M. Divan; Committee Member: J. Rhett Mayor; Committee Member: Linda S. Milor; Committee Member: Ronald G. Harle

State of the art and trends in the monitoring, detection and diagnosis of failures in electric induction motors

Producción CientíficaDespite the complex mathematical models and physical phenomena on which it is based, the simplicity of its construction, its affordability, the versatility of its applications and the relative ease of its control have made the electric induction motor an essential element in a considerable number of processes at the industrial and domestic levels, in which it converts electrical energy into mechanical energy. The importance of this type of machine for the continuity of operation, mainly in industry, is such that, in addition to being an important part of the study programs of careers related to this branch of electrical engineering, a large number of investigations into monitoring, detecting and quickly diagnosing its incipient faults due to a variety of factors have been conducted. This bibliographic research aims to analyze the conceptual aspects of the first discoveries that served as the basis for the invention of the induction motor, ranging from the development of the Fourier series, the Fourier transform mathematical formula in its different forms and the measurement, treatment and analysis of signals to techniques based on artificial intelligence and soft computing. This research also includes topics of interest such as fault types and their classification according to the engine, software and hardware parts used and modern approaches or maintenance strategies