Application of infrared thermography to failure detection in industrial induction motors: case stories

(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising 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] Infrared thermography has been extensively applied over decades to areas such as maintenance of electrical installations. Its use in electrical machinery has been mainly circumscribed to the detection of faults in static machines, such as power transformers. However, with regard to the predictive maintenance of rotating electrical machines, its use has been much more limited. In spite of this fact, the potential of this tool, together with the progressive decrease in the price of infrared cameras, make this technique a very interesting option to, at least, complement, the diagnosis provided by other well-known techniques, such as current or vibration data analysis. In this context, infrared thermography has recently shown potential for the detection of motor failures including misalignments, cooling problems, bearing damages or connection defects. This work presents several industrial cases that help to illustrate the effectiveness of this technique for the detection of a wide range of faults in field induction motors. The data obtained with this technique made it possible to detect the presence of faults of diverse nature (electrical, mechanical, thermal and environmental); these data were very useful to either diagnose or to complement the diagnosis provided by other tools.This work was supported in part by the Spanish Ministerio de Economia y Competitividad and the FEDER Program in the framework of the Proyectos I+D del Subprograma de Generacion de Conocimiento, Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia under Grant DPI2014-52842-P.Lopez-Perez, D.; Antonino-Daviu, J. (2017). Application of infrared thermography to failure detection in industrial induction motors: case stories. IEEE Transactions on Industry Applications. 53(3):1901-1908. https://doi.org/10.1109/TIA.2017.2655008S1901190853

Guest Editorial Special Section on Advanced Signal and Image Processing Techniques for Electric Machines and Drives Fault Diagnosis and Prognosis

© 2017 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] With the expansion of the use of electrical drive sys- tems to more critical applications, the issue of reliability and fault mitigation and condition-based maintenance have consequently taken an increasing importance: it has become a crucial one that cannot be neglected or dealt with in an ad-hoc way. As a result research activity has increased in this area, and new methods are used, some based on a continuation and improvement of previous accomplishments, while others are applying theory and techniques in related areas. This Special Section of the IEEE Transactions on Industrial Informatics attracted a number of papers dealing with Advanced Signal and Image Processing Techniques for Electric Machine and Drives Fault Diagnosis and Prognosis. This editorial aims to put these contributions in context, and highlight the new ideas and directions therein.Antonino-Daviu, J.; Lee, SB.; Strangas, E. (2017). Guest Editorial Special Section on Advanced Signal and Image Processing Techniques for Electric Machines and Drives Fault Diagnosis and Prognosis. IEEE Transactions on Industrial Informatics. 13(3):1257-1260. doi:10.1109/TII.2017.2690464S1257126013

2-D Magnetomechanical Transient Study of a Motor Suffering a Bar Breakage

© 1972-2012 IEEE. The analysis of the vibration response of electrical machines has importance in noise prediction and more recently, diagnosis of electrical faults, especially in the industrial environment, where it is a well-known technique. This work assesses the performance of a strongly coupled two-dimensional (2-D) magnetomechanical approach, as directly available in multiphysics software, for the simulation of an induction machine under heavy operational conditions: a direct-on-line startup. Both healthy and broken bar states are simulated in a time span long enough to allow the detailed study of the varying frequency components. The results yield, in addition to the usual electrical and magnetic quantities, electromagnetic-induced vibration components in the stator. A comparison with current and vibration experimental data is also performed showing a good agreement with variable frequency components and certain limitations concerning their amplitude

Study of thermal stresses developed during a fatigue test on an electrical motor rotor cage

© 2018 Structural defects in the rotor cage of large electrical machines significantly impact their expected operational lifetime. This work presents the results of simulating the thermal stresses developed in a rotor cage during a fatigue test in which a bar breakage was achieved. A combined model featuring electrical, thermal and mechanical stages as well as three different meshes reflecting a progressing narrowing of one of the bars in its junction to the end ring are used for this purpose. The experimentally implemented startup and plug stopping transients are reproduced as well as, for comparison, the stall operation. The resulting stress levels are in agreement with the progression of the damage and concur with the stator measurements. Based on the analysis of the simulated rotor magnitudes, a strategy to diminish the thermal stresses in a damaged cage is proposed

Determination of the Insulation Condition in Synchronous Generators: Industrial Methods and Case Study

[EN] Electrical Machines, and especially Synchronous Generators (SG), take a significant position in Power Generation plants and in Industry Production Lines and their unscheduled outages may have very negative repercussions. One of the main reasons for their failure relies on the degradation of their stator and rotor insulation systems. Although there are several industrial methods that are commonly used for diagnosing the health of such parts, some critical aspects remain unsolved. This paper reviews the different diagnostic methods and techniques that are most commonly used in practice to determine the condition of these two insulation systems in SG, emphasizing their respective drawbacks and analyzing their variants. Consequently, a case study on a SG operating in a Power Plant in Greece which illustrates the application of all these methods is presented.Part of this research was funded by Generalitat Valenciana, Conselleria de Educacion, Investigacion, Cultura y Deporte, under Grant AICO/2019/224. The authors of this article would like to thank Pericles Stratigopoulos, director of the Komotini Power Plant, Public Power Corporation S.A., Greece, for providing the pictures of the stator and rotor and the measurements for this SG.Verginadis, D.; Antonino-Daviu, J.; Karlis, A.; Danikas, M. (2022). Determination of the Insulation Condition in Synchronous Generators: Industrial Methods and Case Study. IEEE Industry Applications Magazine. 28(2):67-77. https://doi.org/10.1109/MIAS.2021.3114659677728

Fault Detection of Circulation Pumps on the Basis of Motor Current Evaluation

2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising 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 work. https://doi.org/10.1109/TIA.2021.3085697[EN] Motor current signature analysis (MCSA) for fault detection has found widespread application, especially for induction motors (IM). The basis of MCSA is the evaluation of a motor¿s current. This analysis is now also used for other motor types and can be used to detect faults of the coupled load. The purpose of this paper is to examine whether MCSA can be used to detect faults in a wet-rotor pump. A total of three faults are examined. The results show that, compared to a healthy pump, all faults could be detected. However, a detailed analysis of frequency components has to be carried out to differentiate the faults. A circulation pump with a maximum power consumption of 1.1 kW was used as the test item.This work was supported in part by the German Federal Ministry for Economic Affairs and Energy within the framework "Entwicklung optimierter Regelungen hydraulischer Systeme in der Gebaudetechnik zur Steigerung der Energieeffizienz von Heizungs-und Klimatisierungssystemen" under Grant 03ET1613B.Becker, V.; Schwamm, T.; Urschel, S.; Antonino-Daviu, J. (2021). Fault Detection of Circulation Pumps on the Basis of Motor Current Evaluation. IEEE Transactions on Industry Applications. 57(5):4617-4624. https://doi.org/10.1109/TIA.2021.30856974617462457

Modern Diagnostics Techniques for Electrical Machines, Power Electronics, and Drives

© 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] For the last ten years, at least three different special sections dealing with diagnostics in power electrical engineering have been published in the IEEE transactions on industrial electronics [1]-[5]. All of them had their specificities, but the last ones, starting in 2011, were more connected to relevant events organized on the topic. In fact, these events have been clearly the only international forums fully dedicated to diagnostics techniques in power electrical engineering. For this particular issue, it has been decided to separate the different submissions into six parts: state of the art; general methods; induction machines (IMs); synchronous machines (SMs); . electrical drives; power components and power converters. The second section includes only one state-of-the-art paper, which is dedicated to actual techniques implemented in both industry and research laboratories. The third section includes three papers on diagnostic techniques not specifically aimed at a particular type of machine. The fourth section includes three papers devoted to diagnostics of rotor faults, two dedicated to stator insulation issues, and four papers dealing with mechanical faults diagnosis in IMs. The fifth section includes papers focusing on different types of SMs. The first two papers deal with wound-rotor SMs, the following three papers are dedicated to permanent-magnet radial flux machines, and the last one deals with permanent-magnet axial flux machines. Regarding the types of faults analyzed, there are three papers devoted to the diagnosis of interturn short circuits in the stator windings, i.e., one dedicated to the detection and location of field-winding-to-ground faults and a paper devoted to the diagnosis of static eccentricities. In the sixth section, two papers investigate issues related to faults in drive sensors, and one is devoted to fault detections in the coupling inductors. The last section includes two papers devoted to diagnosis of faults and losses analysis in switching components of power converters.Capolino, G.; Antonino-Daviu, J.; Riera-Guasp, M. (2015). Modern Diagnostics Techniques for Electrical Machines, Power Electronics, and Drives. IEEE Transactions on Industrial Electronics. 62(3):1738-1745. doi:10.1109/TIE.2015.2391186S1738174562

Advanced Rotor Fault Diagnosis for Medium-Voltage Induction Motors Via Continuous Transforms

[EN] Anumber of field case studies for rotor fault diagnosis on medium-voltage induction motors operating in a petrochemical plant are presented in this paper. The methodology employed is based on analyzing the induction motor startup current with advanced signal processing tools (continuous transforms) that enable a capture of a complete picture of the rotor condition. Indeed, unlike the classical tools that often rely on the detection of few fault frequencies, these new tools allow extraction of the evolution of a wide range of fault components during the startup transient and steady-state evolutions, which enables improved reliability. This is crucial in medium-high-voltage motors, where a false diagnosis may result in significant expense due to inspection, repair, or forced outage. An additional contribution of the study is its immunity to external voltage supply disturbances, which introduce components that are not related to the failure and which are difficult to detect with classical tools. The results of this study prove how the advanced continuous tools enable an improved visualization of the fault components, distinguishing them from the other components that are not linked to the failure.This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology under Grant NRF-2013R1A1A2010370, and in part by the Human Resources Development Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) funded by the Korea Government Ministry of Trade, Industry, and Energy under Grant 20134030200340Antonino-Daviu, J.; Pons Llinares, J.; Lee, SB. (2016). Advanced Rotor Fault Diagnosis for Medium-Voltage Induction Motors Via Continuous Transforms. IEEE Transactions on Industry Applications. 52(5):4503-4509. https://doi.org/10.1109/TIA.2016.2582720S4503450952

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