Iet Electric Power Applications最新文献

{"title":"Induction Motor Multifault Detection Using Machine Learning: Improving Model Accuracy With Current Signal Preprocessing","authors":"Semen Koveshnikov,&nbsp;Nada El Bouharrouti,&nbsp;Alireza Nemat Saberi,&nbsp;Anouar Belahcen","doi":"10.1049/elp2.70160","DOIUrl":"https://doi.org/10.1049/elp2.70160","url":null,"abstract":"<p>Understanding optimal feature engineering for motor diagnostics remains an open research area, as many signal analysis and processing strategies have yet to be systematically explored and explicitly linked to the behaviour of machine learning models. This paper explores optimal parameters and techniques of current signal acquisition and preprocessing for detecting different faults in induction motors using machine learning and motor current signature analysis. Conventional fault detection methods usually advocate for a higher frequency resolution in the motor current spectrum, which requires longer current signal measurements that are difficult and expensive to conduct and process in case of a real-world scenario. Thus, this work aims to identify the limitations to frequency resolution for successful fault diagnosis when applying machine learning algorithms, here, a multilayer perceptron model. The goal is to provide recommendations on signal preprocessing for feature extraction to enhance the performance of the machine learning model. For example, a signal transformation method via signal multirate resampling is evaluated for the improvement of the algorithm accuracy results. The proposed methods boost not only the prediction accuracy but also may refine the system performance when considering industrial applications, as this work outlines in detail the signal acquisition and preprocessing logic. In this paper, the investigated faults include broken rotor bar, bearing fault, misalignment, eccentricity, imbalance, looseness and mixed faults. This article also proposes a new outlook on machine learning feature introspection with scatter plots, which are surprisingly rarely used in the domain of motor condition monitoring but offer a swift access to data insights at the stage of feature engineering.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70160","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147565806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Indirect Measurement Approach of a Uniform Transformer Winding Inductances Using Frequency Response Analysis Data: An Analytical Approach","authors":"Moustafa Sahnoune Chaouche,&nbsp;Faouzi Didi,&nbsp;Aymen Flah,&nbsp;Hamza Houassine,&nbsp;Slim Ben Chaabane,&nbsp;Rachid Sahnoune Chaouche,&nbsp;Mohd Fairouz Mohd Yousof,&nbsp;Mohamed K. Metwaly,&nbsp;Sherif S. M. Ghoneim","doi":"10.1049/elp2.70155","DOIUrl":"https://doi.org/10.1049/elp2.70155","url":null,"abstract":"<p>This article proposes an innovative analytical method that estimates winding inductances directly from measurable frequency response analysis (FRA) data. The method constructs a polynomial function based on the inverse-square sum of short-circuit natural frequencies and equivalent inductance, incorporating a coupling factor that captures the extent of mutual interaction between discs. Unlike earlier numerical and optimisation-based methods that typically involve a large number of inductance parameters, the proposed approach yields a physically meaningful real positive solution for the coupling factor. The approach offers a practical analytical solution for indirectly measuring the self- and mutual inductances of uniform windings, involving the measurement of relevant winding parameters—such as equivalent inductance, short-circuit natural frequencies and series and shunt capacitances—using frequency response impedance data. The method then estimates self- and mutual inductances for uniform windings by solving a generalised polynomial developed for an <i>N</i>-section model, enabling the derivation of all windings' inductances. Experimental validation on isolated transformer windings demonstrated strong agreement between measured and estimated FRA curves, with root mean square error (RMSE) values below <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mn>10</mn>\u0000 <mrow>\u0000 <mo>−</mo>\u0000 <mn>3</mn>\u0000 </mrow>\u0000 </msup>\u0000 </mrow>\u0000 <annotation> ${10}^{-3}$</annotation>\u0000 </semantics></math>. These results confirm that the method offers a practical, traceable and accurate measurement-based solution for inductance estimation, with potential applications in transformer condition assessment and fault diagnosis.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70155","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147564499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Image-to-Image Translation Model for Ultra-Fast Performance Prediction of Permanent Magnet Synchronous Machines","authors":"Mengyu Cheng,&nbsp;Xing Zhao,&nbsp;Guangjin Li","doi":"10.1049/elp2.70161","DOIUrl":"https://doi.org/10.1049/elp2.70161","url":null,"abstract":"<p>Recent advancements in artificial intelligence (AI) and deep learning (DL) have shown great potential in accelerating computational tasks. Notably, image-to-image translation (I2I) has gained significant attention due to its broad applications in computer vision and image processing problems. This paper presents a data-driven I2I model based on conditional generative adversarial networks (cGAN) to predict the performance of an interior permanent magnet synchronous machine (IPMSM). The generator of the cGAN can plot tangential and radial magnetic flux density maps from the input cross-sectional images of an IPMSM with varying geometric features, dimensions, pole-slot configurations and excitations. Additionally, a comparison is made between traditional cGAN networks and a modified multidomain version that incorporates a physics-informed loss function. Model test shows that the proposed method significantly reduces computation time. For a single design, the improvement of evaluation speed is approximately 90.23% compared to the FEA simulation. Besides, the multidomain evaluative model can reduce training time consumption whilst improving the prediction accuracy. Experimental validation indicates that the predicted magnetic flux density maps have an average error of less than 0.13% compared to FEA results. Furthermore, post-processing the generated images enables the calculation of the torque, flux linkage and induced voltage of the IPMSM. The accuracy of performance calculation using the I2I model is also verified against data obtained from FEA software.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70161","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147563844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Suppression of DC Winding Current Harmonics in Wound-Field Machines Under PWM Excitation by Using Active Voltage Injection and LC Low-Pass Filters","authors":"Zhimian Wang,&nbsp;Lai Jin,&nbsp;Zhongze Wu,&nbsp;Wei Hua,&nbsp;Wentao Zhang,&nbsp;Ming Cheng","doi":"10.1049/elp2.70157","DOIUrl":"https://doi.org/10.1049/elp2.70157","url":null,"abstract":"<p>The magnetic field modulation wound-field (MFMWF) machine exhibits good rotor robustness similar to switched reluctance machines. However, the DC winding induced voltage pulsation has been one of the major problems in MFMWF machines. Moreover, pulse width modulation (PWM) excitation further introduces harmonics in the DC winding induced voltage around the PWM frequency and its integer multiples. In this paper, a suppression method composed of active voltage injection and an LC low-pass filter with passive damping is proposed for the first time to suppress the influence of the DC winding induced voltage pulsation, that is, the DC winding current harmonics. To verify the effectiveness of the proposed method, a prototype is built and tested. The experimental results show that the proposed method can effectively improve the suppression capability of the DC winding current control system for both the baseband-order harmonics and the sideband-order harmonics.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70157","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147563843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Magnetic-Thermal Coupling Analysis of the End Region of a Large Steam Turbine Generator in the Phase Advancing State Based on the Improved TSO and SVR Regression Models","authors":"Yonggang Li,&nbsp;Fuchuan Guan,&nbsp;Tianyu Yao,&nbsp;Peng Qi,&nbsp;Minghan Ma","doi":"10.1049/elp2.70141","DOIUrl":"https://doi.org/10.1049/elp2.70141","url":null,"abstract":"<p>The accurate magnetic-thermal analysis of generator end regions under leading-phase operation (LPO) remains challenging due to intensified magnetic field fluctuations caused by strong armature reaction. Conventional methods often struggle to achieve high precision under these conditions. To address this gap, this paper proposes a novel hybrid regression model that integrates an improved Tuna Swarm Optimisation (TSO) algorithm with Support Vector Regression (SVR). This approach represents a significant advancement over existing single-method analyses. The study begins by establishing a high-fidelity 3D magnetic-thermal simulation and a coupled field-circuit-network model for a 320 MVA steam turbine generator. This model is used to compute the stator end magnetic field distribution under various leading-phase depths. The core novelty lies in the application of the improved TSO algorithm to optimise the hyperparameters of the SVR model, creating a robust framework for magnetic field prediction under the complex conditions of LPO. The optimised magnetic field data are then utilised for temperature field analysis. Validation against experimental data from a high-power test platform demonstrates the superiority of the proposed TSO-SVR model. The results show a significant improvement in prediction accuracy compared with conventional methods and other benchmark algorithms, with temperature trends closely aligning with measurements. The primary contribution of this work is the development of a highly accurate and reliable coupled electromagnetic-thermal analysis methodology, which provides a more effective tool for the design and safe operation assessment of generators in LPO, a critical capability for modern power systems with high renewable energy penetration.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70141","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147563312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Speed-Sensorless Model-Free Predictive Torque Control for Induction Motor Drive","authors":"Md. Belal Hossen,&nbsp;Md. Habibullah","doi":"10.1049/elp2.70146","DOIUrl":"https://doi.org/10.1049/elp2.70146","url":null,"abstract":"<p>A speed sensor in a motor drive system decreases the reliability and increases the cost and hardware complexity of the system. In this paper, a speed-sensorless model-free predictive torque control (MF-PTC) scheme has been proposed for an induction motor (IM) drive. An extended Kalman filter (EKF) is employed to estimate the motor speed and thus requirements of a speed sensor and pulse width modulation signals are avoided. The rotor flux is also estimated using the EKF based on the current model of the IM. An ultra-local model is employed instead of the mathematical model of the IM for predicting the current and flux in the prediction step of the proposed MF-PTC. The unknown state of the ultra-local model is estimated using a linear extended state observer. Simulation and experimental results confirm that the proposed controller is robust against motor parameter variations. The speed estimator can estimate the motor speed accurately from the maximum speed down to a minimum of 1 Hz. The controller also demonstrates good performance in terms of torque response, stator flux response and stator current total harmonic distortion under various operating conditions.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70146","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147320836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study of the Overvoltage and Its Distribution Characteristics in an Oil-Immersed Iron-Core Reactor Disconnected by an SF6 Circuit Breaker","authors":"Hongyan Nie,&nbsp;Peitian He,&nbsp;Hongxin Wang,&nbsp;Ziwei Gao,&nbsp;Jian Zhang","doi":"10.1049/elp2.70153","DOIUrl":"https://doi.org/10.1049/elp2.70153","url":null,"abstract":"<p>This paper primarily investigates the patterns of overvoltage changes during an interruption of oil-immersed iron-core reactors by circuit breakers and their distribution along the axial winding of the reactor, which optimises the winding structure. A test platform was established to measure the frequency response curves of the reactor core. Based on the operating frequency parameters of a specific model of a 500 kV oil-immersed iron-core reactor, the variation of the reactor parameters with frequency was studied and a simulation model was constructed. A simulation model of the SF₆ circuit breaker was developed using the Fortran language and a three-phase distributed parameter simulation circuit was constructed for the interruption of oil-immersed iron-core reactors by the SF₆ circuit breaker. The obtained amplitudes and types of overvoltages from the simulations were analysed to determine the patterns of overvoltage variation. Overvoltages of higher amplitude from various types were selected, their distribution on the axial winding of the reactor was analysed and the winding structure of the reactor was optimised to reduce the maximum distribution of interruption overvoltages. The results show that the overvoltages generated by the interruption of the oil-immersed iron-core reactor by the SF₆ circuit breaker are related to the chopping current and operation time lag of the breaker. The largest voltage drop occurs at the “internal shield-continuous transition” along the axial winding of the reactor and adding a small amount of shielding wire at this position can effectively reduce the maximum distribution of overvoltages.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70153","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147315523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on Peak-to-Average Power Ratio Control Method for Switched Reluctance Pulse Generator","authors":"Yanting Liu,&nbsp;Fulin Zhou,&nbsp;Shanshan Yang,&nbsp;Minjun Guan,&nbsp;Chuang Liu","doi":"10.1049/elp2.70144","DOIUrl":"https://doi.org/10.1049/elp2.70144","url":null,"abstract":"<p>Switched reluctance pulse generator (SRPG) demonstrates significant potential for development in pulsed power applications owing to its repetitive frequency pulsed output characteristics. Addressing the different requirements for peak output power of pulse loads and constant loads, the peak-to-average power ratio (PAPR) is taken as the generation performance optimisation parameter. By investigating the power characteristics of the SRPG, the influence of control parameters on the PAPR is studied. A PAPR control method is further proposed. It optimises the turn-off angle to regulate the PAPR and then adjusts the turn-on angle to meet the average output power requirement. The results indicate that under fixed operating conditions, the PAPR is almost unaffected by the turn-on angle but increases with the increase of the turn-off angle. When outputting the same average power, the SRPG can significantly adjust the peak output power through the PAPR control method. It can adapt to the demands of different types of loads flexibly. Experimental results further validate the correctness of the power characteristics and the effectiveness of the PAPR control method in optimising generation performance.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70144","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146199447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harmonic Transient Modelling of Three-Phase Induction Motors Considering Non-Sinusoidal Power Supply","authors":"Jinping Kang,&nbsp;Zhiqiang Wu,&nbsp;Jian He,&nbsp;Guangliang Yang,&nbsp;Dongsheng Li,&nbsp;Jingzhe Tu,&nbsp;Xiangtao Xiao,&nbsp;Tong Liu,&nbsp;Haisen Zhao","doi":"10.1049/elp2.70149","DOIUrl":"https://doi.org/10.1049/elp2.70149","url":null,"abstract":"<p>The increasing penetration of renewable energy sources into power grids introduces significant harmonic components in load-side power supplies. Under nonsinusoidal supply conditions, the applications of conventional reduced-order models of three-phase induction motor (IM) lead to substantial inaccuracy in transient simulations as they are unable to account for these harmonics, adequately. To resolve this issue, this study investigates systematically the applicability of the third- and first-order conventional models for transient simulations considering nonsinusoidal supply conditions. Subsequently, the improved fifth-, third- and first-order equation as well as the corresponding harmonic equivalent circuits of IM are derived considering the nonsinusoidal supply. For an 11, 000 kW IM and a 5.5 kW IM, this study compares the performances of the proposed and conventional reduced-order models in simulating the typical transients including the start-up, suddenly loading, locked-rotor and normal steady-state operations. The results demonstrate that the third- and first-order conventional models are suitable only for calculating speed dynamics while they produce significant errors in the predictions of electromagnetic dynamics. In contrast, the proposed third- and first-order models calculate accurately the electromechanical transients of IMs with nonsinusoidal supply, and the calculated results show excellent agreement with those by the fifth-order reference model. The proposed harmonic models of the 5.5 kW IM and the 11, 000 kW IM are validated with the test results and the finite element simulation results, respectively.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70149","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146199470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Magnetic Field Analysis of Multi-Segment Modulated Pole Motors Based on the Air Gap Domain Multi-Harmonic Method","authors":"Kun Wang,&nbsp;Yong Han","doi":"10.1049/elp2.70148","DOIUrl":"https://doi.org/10.1049/elp2.70148","url":null,"abstract":"<p>This article improves the traditional subdomain model based on the theory of air gap magnetic field modulation and proposes an analytical method for the magnetic field of air gap domain multi-harmonics. The improved model builds on the subdomain model by adding more harmonic coefficients to the air gap domain to comprehensively represent the harmonic characteristics and spatial frequency of the motor's magnetic field. The improved model effectively solves the problem of inaccurate magnetic field results when analysing multi-pole pairs motors using the traditional subdomain model and reduces the matrix dimension during analytical calculations. The computational object in this paper has a large number of pole pairs and multi-segment modulated poles. The analytical results are compared with finite element results and prototype experiments to validate the accuracy of the air gap domain multi-harmonic method. The improved model reduces matrix dimensions and shortens analytical computation time. It may also decrease computational load during iterations, thereby accelerating the iterative process and providing insights for nonlinear magnetic field analysis.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70148","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146206038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}