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Faults in the power system should be detected as soon as possible. Otherwise, some defects in the protection system can result in imposing considerable destructive damage to the system equipment. The excitation system of a synchronous generator plays a significant role in the proper operation and control of the generator. Loss-of-excitation (LOE) may cause harmful effects on both the generator and power system. If LOE is not correctly detected, an unnecessary trip signal may be issued, resulting in the overloading of parallel generators and even a system blackout. Conventional techniques for detecting this fault are based on impedance measurement. Despite the simple structure of these techniques, they are sometimes unable to detect some faults correctly. The presence of flexible alternating current transmission system devices can significantly affect the impedance characteristic of the system and as a result, the operation of impedance relays. In this article, first, LOE and other bugs causing failures and errors in the protection of LOE are simulated in the presence and absence of a unified power flow compensator (UPFC), and parameters with different behavior are determined. Then, the most sensitive parameters are sorted using an intelligent method based on their sensitivity. Once the sort order table is obtained, the first two parameters are applied to a ground data handling neural network method, and LOE is detected. The simulation results show that the proposed algorithm is significantly reliable in detecting LOE faults. Moreover, LOE is detected very quickly in the presence or absence of the UPFC in the system by preventing the tolerance of electrical and mechanical stresses by the machine and system; thus, the maloperation of the protection system is avoided. [ABSTRACT FROM AUTHOR]

Frequency response analysis (FRA) provides valuable information on internal electrical and mechanical faults in a transformer. This information can also be used to diagnose the turn-to-turn fault (TTF) in a transformer winding. This paper concentrates on using numerical indices for the evaluation of FRA to diagnose the TTF severity of the transformer winding. This evaluation is essential for expanding the knowledge toward the interpretation of FRA results. In this paper, the FRA traces of a winding are obtained in the laboratory for a healthy and faulty transformer with various TTF severities. The test results are analyzed using the indices related to all points of FRA characteristic and the indices related to the resonance and anti-resonance points. In this analysis, the possibility of diagnosing the TTF severity is addressed. To confirm the experimental results, simulation models of different windings are implemented to repeat the evaluation. By choosing an appropriate frequency range for the evaluation, the numerical indices demonstrate a monotonic performance versus the fault severity, i.e., the TTF severity can be determined in a transformer winding by assessing the FRA results with numerical indices. [ABSTRACT FROM AUTHOR]

The spoke‐type arrangement of permanent magnets (PMs) in rotor of Vernier PM (VPM) machines was first introduced in a dual‐stator topology to overcome low‐power drawback of VPM machines. However, this structure is mostly applicable for high‐power motor drives. A non‐ferromagnetic spoke array VPM generator with a special rotor structure for small‐scale wind turbine generator is presented. The leakage flux lines tend to be aligned with the main flux routes due to a special design of flux barriers in end portion of PM housings. High torque‐density, low weight, torque‐speed curve with a wide constant torque region, promising efficiency, and power factor are the advantages of the proposed machine. An Equivalent‐Magnetic‐Network (EMN) model is established for predicting the complex behaviour of flux lines and operating quantities of the proposed structure with reasonable accuracy. The contribution of the modelling method includes a special mesh cell for the air‐gap permeance network to more accurately capture the flux routes, continuous positioning method for omitting spikes on post‐processing waveforms due to numerical errors, and a stable solving flowchart with a high convergence rate. The validity of the EMN model is validated by comparing the operating waveforms of the machine with the corresponding waveforms obtained by the finite element and experiments. The cover image is based on the Research Article Design of a non‐ferromagnetic spoke array Vernier permanent magnet generator with iron‐bar based on enhanced equivalent magnetic network model by Mehrage Ghods et al., https://doi.org/10.1049/elp2.12272. [ABSTRACT FROM AUTHOR]

Performance analysis of a linear permanent magnet Vernier machine (LPMVM), which has a complex structure, is mostly based on the finite element methods, while for its optimisation or sensitivity analysis a quick mathematical technique is desirable. This paper introduces an LPMVM and its principles of operation. Then, a mixed subdomain and magnetic equivalent circuit are applied to extract magnetic field equations in various parts of the machine, in which the end‐effect in included. Besides, the electromotive force, thrust force, normal force and electric equivalent circuit are determined. An LPMVM was prototyped and tested to verify the accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

Permanent magnet (PM) machines have gained increasing attention from the industry because of their potential merits over conventional electrical machines. High‐temperature level in electrical machines is a major factor that can adversely impact the performance and health conditions of these machines. These effects need to be minimized to make them competitive with currently operational machines in the industry. It can be done by performing a thorough thermal analysis of the prototype during the design process and proper online thermal monitoring of the machine during the operation stage. Thermal modelling is a powerful tool for achieving such goals in both cases. This paper aims to review the state‐of‐the‐art of thermal modelling techniques and provide a detailed comparison of them in PM machines. The fundamental concepts of heat transfer and sources of heat in PM machines are first discussed. Then, different thermal modelling techniques, including thermal subdomain models (TSMs), lumped parameter thermal networks (LPTNs), finite element models (FEMs), computational fluid dynamics (CFD), reduced order models (ROMs), and hybrid thermal models (HTMs) are introduced and compared. Finally, the utilization of these models in the thermal design, control, and monitoring of PM machines is studied. [ABSTRACT FROM AUTHOR]

Special attention has been paid to two-phase switched reluctance motors (SRMs) as they have fewer power electronics components compared to three- or multi-phase ones. However, their main drawbacks are the lack of starting torque and a predetermined direction of rotation. This paper proposes a new self-starting technique for two-phase SRMs, which has superiorities over the previous approaches. In the proposed topology, the flux paths are shorter, and thus the required magnetomotive force is smaller, which reduces losses. The design procedure is explained. Two- and three-dimensional finite element method (FEM) is employed in the analysis. Also, the motor is prototyped, and two test setups for torque-angle measurement and control study are used. The dynamic behavior of the motor is studied applying single-pulse control and current hysteresis control strategies. The experimental results confirm the results obtained by FEM. Both simulation and experiment results confirm that the proposed topology offers higher efficiency, higher mean torque, and better dynamic behavior compared to two conventional SRMs. [ABSTRACT FROM AUTHOR]

Linear permanent magnet Vernier machines (LPMVMs) is an attractive solution for stroke and direct-drive applications. Several LPMVM topologies have been presented for different applications that operate based on magnetic flux modulation. LPMVMs have some advantages including high force, and torque density at low speeds. This paper introduces a double-excited linear Vernier machine for wave energy conversion. To model the machine, finite element analysis and nonlinear equivalent network model are used. To improve the accuracy of the model and compact the network, a new meshing method is proposed. For better continuity in the output waveforms of the machine, special positioning is utilized. The end-effect is modeled using two separate networks. Finally, the modeling and simulation results are compared with each other and validated experimentally. [ABSTRACT FROM AUTHOR]

Flux‐based fault diagnosis methods have attracted ever‐increasing attention from technical communities because of their potential diagnostic capabilities and ability to overcome weaknesses of the traditional methods such as motor current signature analysis (MCSA). This study reviews recent literature on these methods and addresses their strengths and limitations. Different types of flux sensors that can be used for fault diagnosis applications are also discussed. Flux‐based approaches are classified based on the type of utilised flux into internal (airgap flux) and external (stray flux) methods and compared with each other. The most common faults in both induction machines (IMs) and permanent magnet machines (PMMs), including inter‐turn short‐circuit (ITSC), airgap eccentricity (AGE), rotor broken bars (BRB), and irreversible demagnetisation (IDM) faults, are considered in this review. Finally, research gaps are identified, and some suggestions for future research in this area are provided. [ABSTRACT FROM AUTHOR]

Operation of Vernier machines is based on flux modulation. They have some advantages including maintaining the rated torque in motor applications and the rated output power in generator applications at low speeds, high torque density and relatively low torque ripple due to their magnetic gear property and fault‐tolerance. In recent years, the motor with various topologies has been developed for different applications. Therefore, analysing and monitoring different faults is essential in the design and implementation stages. This study has two main purposes. First, to introduce an accurate frequency index independent of load variations for detecting the turn‐to‐turn short circuit (TTSC) faults in the stator windings of a permanent magnet Vernier machine. Second, modelling the machine in a healthy condition and in the presence of TTSC faults to investigate its effect on machine performance and output characteristics. An analytical model is presented using the modified winding function theory under the TTSC fault by taking into account the effect of stator slots which enhances the accuracy of the air‐gap permeance function estimation. In the process of calculating the fault index, frequency components of the output characteristics of the machine are obtained from the mathematical equations of the magnetic field. It is shown that the proposed indicators are robust against load variations. [ABSTRACT FROM AUTHOR]

Stator and rotor structures, arrangement of permanent magnets (PMs), and type of coils of PM Vernier machines are reviewed and classified. Then, electromagnetic performance and the energy conversion process in the machine are described. Determination of magnetic field distribution and air‐gap permeance of the machine is very complicated than that of other PM machines. Impacts of variations of dimensions in the machine such as the number of modulators on the modulus width and the rotor PMs thickness on the load characteristics (cogging torque, back‐EMF, and power factor) are investigated. In addition, principles of flux modulation machines operation are presented and the shape and dimensions of the modulators are optimized. The two‐phase and four‐phase winding types are used to improve the output power of the machine. Finally, a 150 W PM Vernier generator is designed and prototyped to feed the road speed camera. [ABSTRACT FROM AUTHOR]

The main idea of this paper is to offer a continuous C-cores unique configuration for switched reluctance motor (SRM) and to present an analytical model for its analysis. The advantages of this structure are having a short path for the main part of the magnetic flux, resulting in less core losses and as well as less negative torque. On the other hand, there is less leakage flux in the proposed structure. Another advantage of this structure is that it has a high mean torque compared to conventional structures, so that this increase in mean torque also increases a small amount of torque ripple, which is negligible. However, power density at a constant volume increases relatively much. The proposed SRM is analyzed by the finite element method (FEM) and by employing a magnetic flux density pattern and magnetic fluxes path, its magnetic equivalent circuit (MEC) is obtained. In this MEC model, the main fluxes and leakage fluxes are fully modeled. After its complete analysis, electromagnetics torque, inductance, flux-linkage, mean torque, and peak torque are evaluated. Static and dynamic performances are then determined. Finally, the proposed SRM was prototyped and tested. The experimental results consisting of static torque, flux-linkage, voltage, and current waveforms and input power are compared with the corresponding results in the MEC model and FEM. The comparisons verify the accuracy and validity of the introduced analytical model. Besides, static torque, flux-linkage characteristics, and dynamic performance at a nominal speed of 1000 rpm and the current chopping control mode with chopping 5A under the load of the proposed SRM are compared with the conventional SRM and its merits are observed. [ABSTRACT FROM AUTHOR]

Thermal models are widely used for diagnosing thermal faults, predicting the thermal behaviour, estimating hot spots, and evaluating the loading capacity. This paper uses a new advanced thermal model, thermography method, and computational fluid dynamic separately to obtain the top‐oil and radiator temperatures. The model consists of four thermal points: the ambient, top‐oil, winding, and radiator. The heat transfer phenomena between these points are modelled by nonlinear thermal resistors. Adding the radiator thermal point to the model improves the accuracy. This is shown by comparing the proposed model with the standard and physical thermal models. The proposed thermal model is validated using the experimental results of three distribution transformers. The thermography camera and image processing technique are also employed to take thermal images and analyse them, respectively. By analysing the thermal images with the image processing method, the top‐oil temperature and radiator temperature are obtained. Furthermore, the computational fluid dynamic model is used to analyse and obtain more accurate prediction of the thermal behaviour of the transformer. Finally, it is proposed to detect faults inside the transformer cooling system by comparing the top‐oil and radiator temperature from two methods presented, that is, advanced thermal modelling and thermography with image processing. [ABSTRACT FROM AUTHOR]

• The impacts of UPFC on the conventional protection scheme is scrutinized. • Features are extracted based on simulation observance and combined with SOM method. • Classification is carried out with LVQ NN. • Proposed method compared to conventional impedance based approach. • The proposed scheme improves the LOE protection function in presence of UPFC. Loss-of-excitation (LOE) conditions may cause devastating effects on both the generator and power system. If LOE is not meticulously detected, two dangerous events may emerge: 1. unnecessary trip signal, 2. not detecting this abnormal condition or detecting it with time delay. Both mentioned flaws have considerable harmful consequences on the generator and power system. Conventional techniques for detecting LOE conditions are based on impedance measurement. The presence of flexible alternating current transmission (FACT) system devices can considerably affect the impedance characteristic of the system and as a result, the operation of impedance-based relays. This paper simulates LOE and stable power swing (SPS) conditions causing failures and errors in the LOE protection in the presence or absence of a unified power flow compensator (UPFC), and parameters with different behaviors are determined. Then, the most sensitive parameters are combined using an intelligent method. The single parameter, achieved from a combination of features in the previous process, is applied to a learning vector quantization (LVQ) neural network. The LVQ is a type of artificial neural network that is based on a prototype supervised learning classification algorithm and trained its network through a competitive learning algorithm. The simulation results show that, in a single machine infinitive bus (SMIB) test system, R-X directional scheme has 2 mal-operations and the proposed algorithm has no mal-operation without UPFC in the system. With UPFC in the system, the R-X directional scheme has four mal-operations and the proposed algorithm has no mal-operation. In the IEEE 9-bus test system, the R-X directional scheme has five mal-operations and the proposed algorithm has no mal-operation. Moreover, applying the proposed algorithm, LOE is detected very quickly in the presence or absence of the UPFC in the system and this approach prevents electrical and mechanical stresses enforced to the machine and power system. © 2017 Elsevier Inc. All rights reserved. [ABSTRACT FROM AUTHOR]

Synchronous generator (SG) plays a vital and critical role in the power system by supplying electric power to consumers. Various faults in SGs can cause some catastrophic events such as power disruption or blackout. These faults can be classified into two electrical and mechanical faults. Short circuit in stator windings and field winding are electrical fault while bearing, static/dynamic eccentricity, and broken damper bars faults are mechanical one. Unlike the induction machines, there are no much researches in SGs condition monitoring owing to its complex behaviour against the faults. Herein, the SG modelling approaches are presented briefly to elaborate shortcoming and challenging issues in the modelling, and then a comprehensive review of various electrical and mechanical fault detection methods is presented. [ABSTRACT FROM AUTHOR]

Summary: Although Vernier machines have been introduced a long ago, their description, applications, and design improvement have been recently proposed. This paper reviews different types of linear Vernier machine. Their description and theoretical base of the performance are presented. The performance of the motor is improved by reducing the cogging force, increasing the power factor, and enhancing force density. Stator and translator structures, the arrangement of magnets, and the type of coils of permanent magnet (PM) Vernier machines are reviewed and classified. Then, the electromagnetic performance prediction and energy conversion process in the machine is described. The magnetic field distribution and air gap permeance analysis indicate that such analysis is very complicated than that of other PM machines. Impacts of variations of dimensions in the machine such as the number of modulators on the modulus width and thickness of the mover PMs on the load characteristics (cogging torque and Back‐EMF) are addressed. Besides, principles of operation of flux modulation machines are presented and the shape and dimensions of the modulators are optimized. Finally, a 150 W linear PM Vernier generator is designed and prototyped to the energy harvested by the ocean wave. [ABSTRACT FROM AUTHOR]

Armature reaction is considered as one of the challenging problems in on-load permanent magnet (PM) motors. Reducing the undesirable impacts of the armature reaction is necessary to improve the PM motors performance. The ironless stator PM motor is known as an appropriate choice for low armature reaction. Although in these motors, disturbing high-order harmonics of armature reaction are removed, improper winding distribution still causes asynchronous field harmonics. Choosing the number of poles and slots leads to various structures with different armature windings for ironless stator PM motors. Impacts of armature reaction upon the performance of the motors with different structures are addressed in this article. This is done using precisely and quickly by a combined analytical model. This model can model the PMs magnetic fields, the air gap magnets field, and the armature reaction field. The finite element modeling (FEM) results confirm the accuracy of the proposed analytical model. Then, the analytical method and FEM are used to predict the performance of the ironless stator PM motors with the different numbers of poles and slots. This makes it possible to suggest an appropriate number of poles and slots for lower armature reaction, lower disturbed voltage harmonics, lower torque ripple, higher output power, and higher winding distribution factor. [ABSTRACT FROM AUTHOR]

Switched reluctance motors (SRMs) have a robust and simple structure, high reliability because of the absence of magnetic field source on rotor, low cost and simple cooling system. However, conventional SRMs confront with some challenges such as low mean torque, low torque density and high torque ripples. For wider applications of SRM, the above-mentioned drawbacks must be mitigated. One possible method is changing the structure of SRMs. In this article, a novel 12/14 three-phase SRM with connected C-core structure is introduced which has a short path for the main flux of stator teeth. This brings about core loss reduction. On the other hand, both teeth of the stator phase in C-core develop a positive torque during the movement of the rotor from the unaligned position to the aligned position; this enhances the torque, the mean torque and torque density of the proposed SRM, keeping the volume fixed. Finally, the proposed SRM was prototyped and tested and its torque/rotor angular position characteristic was measured. To verify the novelty and merits of the proposed SRM, its mean and peak torque, torque density, core losses and torque ripples were compared with those of an optimized 12/8 three-phase conventional SRM and a significant match was achieved. [ABSTRACT FROM AUTHOR]

Permanent magnet vernier generators (PMVGs) are suitable for meeting power concussion requirements of traffic enforcement cameras and traffic‐driven applications. In this study, the performance of PMVGs at no‐load and full‐load are analysed in healthy machines and machines under different types of mechanical faults including static eccentricity, dynamic eccentricity, inclined rotor, and run‐out faults. Furthermore, an analytical model is developed to estimate the air‐gap permeance and the induced voltages in the healthy generator and generator under the above‐mentioned mechanical faults. Then, the performance of the generator is predicted using a two‐dimensional and three‐dimensional time stepping finite‐element method. Finally, from the stator current spectrum of the PMVG under dynamic eccentricity fault, the amplitude of the side‐band components with a specific frequency pattern is extracted and compared with experimental results. [ABSTRACT FROM AUTHOR]

The electric power transformer is a vital apparatus in power systems, and failure prognostics is significant for the protection of this asset. In addition to the asset damage, its unexpected failure would interrupt power delivery and jeopardize the stability of the system. There are several fault diagnosis methods introduced for the detection of this kind of fault; however, their functionality is for the postfault condition when the asset is already damaged, and the operation of the system is interrupted. Electric insulation deteriorations make the transformers susceptive to faults due to thermal and electrical stresses. In this article, the impact of early stages insulation deteriorations on the temperature inside the transformer is studied using a finite-element electromagnetic–thermofluid method and based on the observations an online sensor-based decision-making predictive fault diagnosis approach is proposed. Finally, the results are experimentally verified. [ABSTRACT FROM AUTHOR]

This paper presents surrogate-model based optimization for synchronous reluctance motor (SynRm) with transversally laminated rotor. A radial basis function (RBF) model with 12 input variables and three outputs is first trained. A dataset is obtained using finite element method to estimate parameters of RBF model. By building RBF model, the RBF network can predicts the outputs of the SynRm with good accuracy Using non-dominated sorting genetic algorithm (NSGA II), pareto front is obtained. The SynRm is designed to maximize the maximum developed torque and power factor of the motor with constrained torque ripple. [ABSTRACT FROM AUTHOR]

Thermal conditions of power transformers in abnormal operating conditions such as harmonic loads can be considered as a critical case. In this study, thermal analysis of transformer and additional imposed heat on it, caused by non‐linear loads, are addressed. For this purpose, an appropriate thermal equivalent circuit is used in which temperature of different parts of oil‐immersed power transformers are obtained for harmonic loads. The losses of various components of transformer as heat‐generating sources are estimated. At this end, an appropriate three‐dimensional finite element method is applied to estimate the losses of different parts of transformer. To keep the transformer temperature rise around the permissible value, the transformer is derated. Transformer derating based on the IEEE Std C57.110–2008 recommendation considerably reduces the transformer loading capability. Therefore, this study introduces a new technique for derating of transformer for harmonic loads. This enhances the transformer thermal limits and transformer loading capacity. [ABSTRACT FROM AUTHOR]

Single‐sided linear induction motors (SLIMs) are used in maglev levitation systems for propelling purpose. The reasons for such usages are their capability in direct drive applications with very good dynamic performance, high reliability and high flexibility in trajectory generation. High‐performance requirements of the machine demand a high saliency ratio resulting in small air gap length along the direct axis. Therefore, the air gap symmetry in the primary side and consequently the air gap asymmetry fault diagnosis is essential for the system maintenance. In this study, the air gap asymmetry fault in a SLIM is diagnosed. Since the precise definition of the air gap asymmetry fault and fault severity has not been so far introduced in the relevant literature, they are given here. The proposed fault index is the amplitude of the sideband components of the current with a particular frequency pattern. First, mathematical analysis of magnetic field is proposed, then, fast Fourier transform is applied to the current waveform in the SLIM. The spectrum of the SLIM current in the healthy and faulty cases under different loads is obtained. Time‐stepping finite element method is applied to simulate the healthy and faulty motor. Experimental results are verified by the introduced theoretical index[AQ ID=Q1]. [ABSTRACT FROM AUTHOR]

—To insure the health of power transformers insulation, its heat distribution in different operating conditions must be determined. In extended thermal equivalent circuits (TECs), less attention has been paid to losses and temperature distribution of different parts such as core, tank and metallic regions of transformer. Most previous works, hot-spot temperature of winding and top-oil were considered by available no-load and on-load losses of transformer. This paper extends the TEC to be able to evaluate fully the different operating conditions of transformer. Estimation of losses of different elements of transformer as heat generating source and thermal parameters of transformer are introduced as two major challenges of the proposed model. At this end, an appropriate three-dimensional finite element method is used to estimate the losses of different components of power transformer. In addition, to identify the transformer thermal parameters, a genetic algorithm is used by searching in chosen measurements. Finally, the results obtained by the TEC are compared with IEEE-Annex G method and measured temperature and high accuracy of the proposed model in temperature estimation in different parts of transformer are shown. [ABSTRACT FROM AUTHOR]

There is always uncertainty in industrial manufacturing. These uncertainties have an undesirable impact on the products if deterministic optimization approaches are employed. In order to have products as desired, uncertainties must be quantified in the design process. This paper presents a robust design optimization of an outer rotor surface mounted permanent magnet motor with particular application in the hybrid vehicle using the design for six-sigma methodology. Due to very long computational time of robust optimization, a ten high-dimensional surrogate model of the system using the Box–Behnken response surface methodology (RSM) is integrated with the particle swarm optimization (PSO). This causes a significant improvement in the effectiveness and efficiency of optimization. The results acquired from RSM are verified by their simulation using the finite-element method, and the accuracy of RSM is proved. Finally, the deterministic and robust optimized motors are simulated in mass production using Monte Carlo analysis, and six-sigma quality achievements are demonstrated. [ABSTRACT FROM AUTHOR]

The electric power transformer is a vital apparatus in power systems, and failure prognostics is significant for the protection of this asset. In addition to the asset damage, its unexpected failure would interrupt power delivery and jeopardize the stability of the system. There are several fault diagnosis methods introduced for the detection of this kind of fault; however, their functionality is for the postfault condition when the asset is already damaged, and the operation of the system is interrupted. Electric insulation deteriorations make the transformers susceptive to faults due to thermal and electrical stresses. In this article, the impact of early stages insulation deteriorations on the temperature inside the transformer is studied using a finite-element electromagnetic–thermofluid method and based on the observations an online sensor-based decision-making predictive fault diagnosis approach is proposed. Finally, the results are experimentally verified. [ABSTRACT FROM AUTHOR]

Eccentricity fault with 10% severity is probably the only existing fault in a brand new healthy electrical machine that is acceptable as a manufacturing tolerance. This fault can be developed due to a continuous pull between stator and rotor, even in a de-energized machine. So, it must be diagnosed, and its severity monitored. The authors introduced and criticized various indices for eccentricity fault diagnosis. Advantages, drawbacks, and ambiguous points of each index and potential ground for improvement of these techniques are addressed. Moreover, different eccentric PM machine modelling techniques are reviewed and environmental factors affecting the eccentricity fault detection process are discussed. This survey covers all direct current and alternating current PM machines. It provides information about the researches performed since 1986 and it is helpful to newcomers to this field, artisans, and protection system designers. Considering the given information, the readers achieve enough understanding of the weaknesses and strong points of each eccentricity fault diagnosis index. Then, these indices are evaluated through assigning weight coefficients under various scenarios. Interested individuals can modify these weight coefficients based on the specifics of the application and decide which index is the most appropriate. [ABSTRACT FROM AUTHOR]

This paper addresses a simple and computationally efficient dynamic model for brushless permanent magnet (PM) motors under PM demagnetization faults. The impact of stator slots and spatial disposition of the windings are taken into account to improve the accuracy of a lumped-parameter $abc$ model. This model is suitable for tracking the dynamic behavior of fault components, as it can be accompanied by any control scheme and/or be used for model-based fault detection schemes. In addition, parameters of this model can be automatically tuned by an optimization process in the offline phase of the healthy machine. Finite-element simulations are carried out for proving the effectiveness of the proposed model. Verification is done in both time and frequency domains for four PM motors with different rotor and stator configurations. The simulation results are experimentally verified. [ABSTRACT FROM AUTHOR]

High temperatures may damage power transformers. These problems leading to the high temperature are more revealed under non‐rating operating conditions such as unbalanced supply voltage. The aim of the present study is thermal analysis of such supply and obtaining its temperature distribution. Existing thermal analysis methods through thermal equivalent circuit (TEC) have some drawbacks; in these models, thermal parameters of different regions of transformer such as core, tank, metallic parts and winding are not defined. On the other hand, those models are not applicable for thermal analysis of transformer with unbalanced supply voltage. Here, a novel TEC model is proposed which is able to define temperatures of different components of oil‐immersed power transformers individually under unbalanced supply voltage. The merit of the introduced model is that losses of different parts of transformer are considered as heat generating sources which are used as the inputs of thermal model. At this end, a three‐dimensional finite‐element method is suggested which is able to estimate the losses of different parts of power transformer. Finally, the results of applying the TEC to the transformer are compared with the temperature distribution of finite‐element modelling and high accuracy of the TEC model in estimation of the temperatures of different regions are emphasised. [ABSTRACT FROM AUTHOR]

Doubly‐fed induction generator (DFIG) is the dominant technology in the wind energy market. Rotor inter‐turn short‐circuits (RITSCs) and unbalanced rotor resistance (URR) are the main types of rotor electrical asymmetries in DFIG. The URR has already been considered as an electrical fault or asymmetry in the rotor of DFIG. Although the RITSC introduces URR into the rotor circuit its consequences are not similar due to the structure of the machine and presence of current controllers in the DFIG system. In this study, both RITSC and URR are proposed and compared, and the detection of these faults was performed using appropriate indices in the stator current, reactive power, and rotor modulating voltage signals, which are available in the control system of the DFIG. Furthermore, it is supposed that the discrimination between these two types of faults is feasible by utilising proper fault indices at various operating regions of the wind turbine. The performance of the defined fault indices, for different fault severities, is verified using an experimental setup with the DFIG operating under several conditions such as different power injection into the grid and different rotor speeds, including sub‐synchronous and super‐synchronous operation. [ABSTRACT FROM AUTHOR]

Linear-machine-based direct-drive systems are attracting extensive attention for many industrial applications including wave energy conversion and railway traction. By using a linear machine, the complexity of linear motion systems is considerably reduced due to the elimination of the rotary to linear conversion mechanism. In this paper, a novel linear stator spoke-type permanent magnet (PM) vernier (LSSPMV) machine is presented in which the surface-mounted radial magnets used in conventional linear stator-PM vernier machines are replaced by spoke-type magnets that are magnetized parallel to the direction of motion. The proposed machine adopts a non-magnetic space between PMs and stator pole shoes decreasing the leakage flux and leading to higher flux linkage of armature winding. After designing the proposed LSSPMV machine and comparing it with its existing counterpart, the finite-element method results reveal that the thrust force density and the efficiency of the proposed machine are higher than that of the existing one as a result of utilizing spoke-type PMs. [ABSTRACT FROM AUTHOR]

Transformers are vital components of power systems as they are situated between energy generation and consumers and their failure disrupts the use of electrical energy. Therefore, diagnosing an incipient fault is essential in avoiding hazardous operating conditions and minimizes downtime cost. In transformers, faults take place due to electrical or thermal stresses that cause insulation decomposition in transformers. In oil-filled transformers, insulations are cellulose and oil, and the products of the insulation decomposition are gases which can be dissolved in the oil. Therefore, dissolved gas analysis (DGA) can be used for fault diagnosis in oil filled transformers. In this paper, DGA interpretation methods, conventional and intelligence, are investigated and compared. For evaluating consistency and accuracy of the methods, "No Result" cases are not considered. It can help the newcomers to this field to have access to a comprehensive comparison about the application of computational intelligence and conventional methods in transformer fault detection using DGA. [ABSTRACT FROM AUTHOR]

In this paper, an approach for tooth localized fault detection in the sun gear of a planetary gear, using the measured mechanical torque and the stator current of a wound rotor induction generator (WRIG), is proposed. A theoretical background is developed to demonstrate that the faulty sun gear produces periodic fault signatures in the mechanical torque and consequently fault-related frequencies in the stator current of the WRIG. The employed technique needs knowledge of mechanical system torsional natural frequencies, which aid in identifying the most sensitive fault characteristic harmonics in both mechanical torque and stator current spectra. It is illustrated by simulation and experimental results that the amplitude of these harmonics can be used as a fault index for diagnosis of tooth localized defect in planetary gears. A test rig based on a 5.5 kW WRIG, shaft connected to the sun gear of a planetary gear through a high-speed shaft and couplings, was utilized for validation of the proposed technique. [ABSTRACT FROM AUTHOR]

This paper presents a method for modeling the effects of static eccentricity, dynamic eccentricity, and mixed eccentricity faults on the electromotive force (emf) of the surface-mounted permanent magnet generators (SMPMGs). The model is based on the combination of conformal mapping method (complex relative permeance) and eccentricity relative air gap permeance and it presents explicit formulas for no-load magnetic field distribution, magnetic flux, and emf in SMPMGs under different eccentricity fault types, some have not been so far considered elsewhere. The analytical and also numerical results show that there are some side-band components in the emf signature which can be used as eccentricity fault index. Analytical results validate by time-stepping finite element method (TSFEM) results. [ABSTRACT FROM AUTHOR]

This paper presents an inductance-based method for detection of inter-turn fault in permanent magnet synchronous machines (PMSM). The reason for using inductance for fault detection and its severity estimation is the obvious impact of the fault on the inductances. This fault reduces the effective number of turns and therefore inductances. The PMSM is modeled using magnetic equivalent circuit (MEC). This method takes into account the impacts of stator teeth, rotor yoke, and stator winding distribution precisely. So, it is shown that the MEC method is superior to other analytical methods such as winding function. The governing equations in different parts of the machine are proposed, and the MEC equations of the PMSM are developed. First, healthy and faulty PMSM is simulated using MEC for different severities of the fault. In the 2nd stage, the required analytical equations for self-inductance and mutual inductance estimation are extracted, and the impact of the fault severity upon these inductances is determined. Finally, inter-turn short-circuit fault is detected, and its severity is determined using the amplitude of the inductance of the faulty phase. Simulation results and the proposed fault diagnosis method are validated using finite elements method. [ABSTRACT FROM AUTHOR]

Wide application of wind energy in the world towards reduction of global warming, have made the low cost maintenance of these turbines very important. Basically, mechanical faults such as gear‐box faults in these turbines lead to a long down time and consequently heavy financial loss. Generally, these faults cause eccentricity in the generator air gap, so by its early detection the fault can be largely prevented. In this paper, eccentricity fault detection is studied in doubly‐fed induction generator (DFIG) which is the most established generator in wind turbines and also is more prone to mechanical faults compared to other technologies. One of frequency components of reactive power is introduced as eccentricity fault index. As the reactive power is always evaluated in the control system, there is no need to include a new hardware for fault detection. Finite elements method is used to model the wound rotor induction machine (WRIM) which is coupled with closed‐loop control system. Following the validation of the model in the healthy case experimentally, eccentricity under different operating conditions is included in the modeling. Finally, a simple procedure based on simple signal processing methods is introduced for eccentricity fault diagnosis considering the operating conditions of the wind turbine. [ABSTRACT FROM AUTHOR]

Permanent magnet (PM) machines are widely used in industrial processes due to their merits such as high power density and torque and low losses (high efficiency). These machines operate frequently under harsh conditions; therefore, they expose different types of faults. These faults can be diagnosed in initial stages using different techniques and prevent the faults' progress to catastrophic stages. One of the most important PM machine faults in terms of occurrence rate is demagnetization fault, whose causes can be heat, electrical, environmental or combinations. This may lead to efficiency drop, poor performance, and low reliability of the system. This paper attempts to review and summarize the demagnetization fault diagnosis methods in PM machines. First the fault generating factors and their impacts on the performance of the motor are discussed. Then, the recently developed techniques for demagnetization fault under stationary and nonstationary conditions in two separate sections are addressed. Presented methods are compared; their weaknesses and strengths are noted. Finally, suggestions for further research are proposed. [ABSTRACT FROM PUBLISHER]

Transformers are the most important equipment in power systems, and their failure can cause serious problems. In order to avoid hazardous operating conditions and reduce outage rates, fault detection in the incipient stage is necessary. Incipient faults cause thermal or/and electrical stresses on the transformer with a major consequence on insulation decomposition. The insulation decomposition causes the evolution of gases which can be dissolved in oil. Dissolved gas analysis (DGA) interpretation is one of the main techniques used for fault diagnosis in oil-immersed transformers. In this paper, DGA interpretation is evaluated in detecting different faults and the techniques considered as conventional methods of DGA are investigated. The evaluation is based on DGA data obtained from oil samples of real transformers. [ABSTRACT FROM PUBLISHER]

Inter‐turn fault (ITF) of stator winding is a very sensitive and critical fault in permanent magnet motors. If this fault is not diagnosed on‐time, it can quickly expand and generate serious damage and even full damage to the motor. So, realisation of this fault, its impact on the motors and finally its diagnosis methods are essential and has high priorityfor users of the motors. This study presents the trend of the negative impacts of the fault on the performance of the machine. Available indexes for this fault detection are introduced and described in details. By analysing these indexes, their merits and drawbacks, limitations and ambiguous points are extracted. Finally, these indexes are compared and the best and worst indexes are introduced. Moreover, one of the most used index and the simplest one will be simulated in order to show capability of a new current‐based ITF diagnosis index. [ABSTRACT FROM AUTHOR]

Supplying non-linear loads causes increased losses in transformers which eventually leads to their reduced life spans. Therefore, transformers are derated in order to protect them against premature loss of life. To do this, load losses including ohmic loss and winding eddy current (WEC) loss need to be estimated. This study suggests an improved analytical approach using finite element method (FEM) which includes all material characteristics and geometrical structures in order to calculate WEC loss under non-sinusoidal load current in each winding individually. By adopting this procedure, harmonic loss factor as a dominant parameter in transformers derating is estimated. By emphasising the region in which the maximum WEC loss occurs, an additional factor (FMECL) based on the physical phenomena involved is introduced using FEM. On the basis of the aforementioned concepts, a new relationship is presented for transformer derating. Ultimately, the suggested method and the IEEE standard are applied to derate a distribution transformer and the results are discussed. In addition, the proposed method is validated using a thermal model and its advantages over the IEEE derating method is presented. [ABSTRACT FROM AUTHOR]

Supplying non‐linear loads causes increased losses in transformers which eventually leads to their reduced life spans. Therefore, transformers are derated in order to protect them against premature loss of life. To do this, load losses including ohmic loss and winding eddy current (WEC) loss need to be estimated. This study suggests an improved analytical approach using finite element method (FEM) which includes all material characteristics and geometrical structures in order to calculate WEC loss under non‐sinusoidal load current in each winding individually. By adopting this procedure, harmonic loss factor as a dominant parameter in transformers derating is estimated. By emphasising the region in which the maximum WEC loss occurs, an additional factor (FMECL) based on the physical phenomena involved is introduced using FEM. On the basis of the aforementioned concepts, a new relationship is presented for transformer derating. Ultimately, the suggested method and the IEEE standard are applied to derate a distribution transformer and the results are discussed. In addition, the proposed method is validated using a thermal model and its advantages over the IEEE derating method is presented. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of a wound rotor induction motor (WRIM) under rotor inter-turn short circuit (SC) fault. Magnetic equivalent circuit (MEC) and finite elements method (FEM) are used to model the machine. Impacts of the fault on the signals of the machine including rotor current, stator current, and developed torque of the motor are addressed. Current of SC turns is also the signal that is considered here. A method based on the MEC is used to estimate different inductances of WRIM in which the impact of yokes, stator and rotor tooth, windings distribution and also core saturation are included. The obtained inductances are compared with that of the FEM and effect of the SC turns on the inductances are investigated. Finally, the fault is diagnosed using Fourier transform of the stator current and verified by experimental results. [ABSTRACT FROM AUTHOR]

Demagnetization fault is the most widespread fault in permanent magnet synchronous motors (PMSMs). Diagnosing this fault and extracting appropriate indexes for the PMSM are proposed and discussed in this paper. The index-extracting techniques and their advantages, disadvantages, and significant ambiguities are proposed, and it is emphasized how these ambiguities can be eliminated. This can help the newcomers to this field as well as designers and manufacturers of protection and fault diagnosis industry. In light of this information, the readers will have a full view on different aspects of each index. An optimum index can be chosen based on the sensitivity of application and the cost of index implementation. [ABSTRACT FROM AUTHOR]

Induction machines (IMs) are widely used in different applications. Unpredicted breakdown of these machines usually leads to costly downtimes and repairs. These expenses can be minimized using proper condition monitoring techniques. Eccentricity fault is one of the widespread faults causing machine malfunction; its detection could be useful for prevention of harmful consequences. In this paper, different works on eccentricity diagnosis of IMs with different types of supply have been reviewed. It commences from the simplest open-loop machine, and by considering torque variation and inverter switching gradually turns to complicated closed-loop machine with different control strategies. While in most cases, current is used for condition monitoring, in some instances power and voltage are employed for fault diagnosis. Due to extensive use of IMs in wind turbines as doubly-fed induction generator (DFIG), in addition to declaration of importance of eccentricity fault diagnosis in DFIG, detection of eccentricity fault in DFIG is also reviewed. [ABSTRACT FROM AUTHOR]

The increasing application of non‐linear loads in power system causes additional losses in transformers resulting in premature damage. Manufactures and users of transformers realise the importance of this phenomenon and it is vital to adopt a procedure to prevent it thereby enhancing the reliability of power system. To achieve this, the most common method is derating of transformers. This paper intends to review derating of transformers under non‐sinusoidal operation, for which all available approaches are classified into four major methods including IEEE recommended, analytical, experimental and finite elements based method. For each method, the fundamental theory, significant factors related to derating, test techniques as well as advantages and disadvantages are discussed. The methods are then evaluated and compared with each other from different points of view. Moreover, the overall trend of a more precise derating method is suggested. This review clarifies the research areas which require attention in the future to advance the subject. [ABSTRACT FROM AUTHOR]

This article presents the three-dimensional modeling of an induction motor using a magnetic equivalent circuit. The main goal of introducing the three-dimensional model is to include axial fluxes in the machine equations. Furthermore, enhancement of the precision of teeth flux estimation and air-gap permeances, as the most important and dominant factors, is another achievement of this model compared to that of the two-dimensional model. This increases the accuracy of the estimated torque. Although it is possible to include the impact of the bar skew in the two-dimensional modeling using a magnetic equivalent circuit, this can be included more precisely in the three-dimensional model due to the three-dimensional nature of the bar skew. Therefore, the three-dimensional model as an efficient method with rapid computations and suitable precision is used for modeling various types of eccentricity. It is shown that the three-dimensional model results are closer to the experimental results compared to that of the two-dimensional model. This confirms the merit of the three-dimensional model. Also, this method can be a proper substitution to the finite-element method in modeling a machine under fault and fault diagnosis. [ABSTRACT FROM PUBLISHER]