34 research outputs found

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

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    © 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

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    © 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

    Particle filter-based estimation of instantaneous frequency for the diagnosis of electrical asymmetries in induction machines

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    "© 2014 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.” Upon publication, authors are asked to include either a link to the abstract of the published article in IEEE Xplore®, or the article’s Digital Object Identifier (DOI).Fault diagnosis of induction machines operating under variable load conditions is still an unsolved matter. Under those regimes, the application of conventional diagnostic techniques is not suitable, since they are adapted to the analysis of stationary quantities. In this context, modern transient-based methodologies become very appropriate. This paper improves a technique, based on the application of Wigner Ville distribution as time frequency decomposition tool, using a particle filtering method as feature extraction procedure, to diagnose and quantify electrical asymmetries in induction machines, such as wound- rotor induction generators used in wind farms. The combination of both tools allows tracking several variable frequency harmon- ics simultaneously and computing their energy with high accu- racy, yielding magnitudes and values similar to those obtained by the application of the fast Fourier transform in stationary operation. The experimental results show the validity of the approach for rapid speed variations, independently of any speed sensor.Climente Alarcon, V.; Antonino Daviu, JA.; Haavisto, A.; Arkkio, A. (2014). Particle Filter-Based Estimation of Instantaneous Frequency for the Diagnosis of Electrical Asymmetries in Induction Machines. IEEE Transactions on Instrumentation and Measurement. 63(10):2454-2463. doi:10.1109/TIM.2014.231011324542463631

    Advanced Analysis of Motor Currents for the Diagnosis of the Rotor Condition in Electric Motors Operating in Mining Facilities

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    © 1972-2012 IEEE. Predictive maintenance of electric motors is a topic of increasing importance in many industrial applications. The mining industry is not an exception; many electric motors operating in mining facilities are critical machines, and their unexpected failures may imply significant losses and can be hazardous for the users. Due to these facts, an increasing research effort has been dedicated to investigate new techniques that are able to provide a reliable diagnostic of the motor condition. Over recent years, monitoring of electrical quantities (e.g., motor currents) has emerged as a very attractive option for determining the health of several motor parts (rotor, eccentricities, bearings) due to its very interesting advantages: possibility of remote motor monitoring, noninvasive nature, simple application, broad fault coverage, etc. The traditional methods based on the analysis of motor currents during a steady-state operation [motor current signature analysis (MCSA)] are being complemented when not replaced by more reliable approaches. This paper applies an innovative transient-based methodology to several case studies referred to large motors operating in mining facilities. The results prove how this modern methodology enables us to overcome some important drawbacks of the classical MCSA, such as its unsuitability under varying speed conditions, and may provide an earlier indication of rotor electrical asymmetries under such working conditions
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