Fault detection in induction motors and the impact on the kinematic chain through thermographic analysis

Garcia-Ramirez, A. G.; Morales-Hernandez, Luis A.; Osornio-Ríos, Roque Alfredo; Benítez-Rangel, Juan P.; García-Pérez, Arturo; Romero-Troncoso, René de Jesús

doi:10.1016/j.epsr.2014.03.031

Cited by 84 publications

(26 citation statements)

References 29 publications

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“…[26] which presents a methodology based on segmentation of thermographic images for fault diagnosis in induction motors. According to the authors, this methodology diagnoses broken bars in the rotor, bearings, mechanical unbalance, misalignment and also unbalance voltage.…”

Section: Introductionmentioning

confidence: 99%

A comprehensive evaluation of intelligent classifiers for fault identification in three-phase induction motors

Palácios

Silva

Goedtel

et al. 2015

Electric Power Systems Research

106

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Section: Introductionmentioning

confidence: 99%

A comprehensive evaluation of intelligent classifiers for fault identification in three-phase induction motors

Palácios

Silva

Goedtel

et al. 2015

Electric Power Systems Research

106

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“…Works on the study of heating processes and on the basis of mathematical models are displayed in scientific works on the optimization of energy consumption [1], which requires quite serious material costs and cannot be used as a universal tool. Other work to optimize the control of the temperature characteristics of the engine [2] is aimed at solving one existing problem and does not cover the problem as a whole. In [2], the authors' attention is directed to finding solutions for monitoring current temperature parameters when using a thermal model of an induction machine.…”

Section: Fundamental and Applied Physicsmentioning

confidence: 99%

“…Other work to optimize the control of the temperature characteristics of the engine [2] is aimed at solving one existing problem and does not cover the problem as a whole. In [2], the authors' attention is directed to finding solutions for monitoring current temperature parameters when using a thermal model of an induction machine. The findings in [2] show that it is necessary to create a general mathematical model for monitoring engine temperature parameters.…”

Section: Fundamental and Applied Physicsmentioning

confidence: 99%

Investigation of the Heating Processes and Temperature Field of the Frequency-Controlled Asynchronous Engine Based on Mathematical Models

Зубенко

Petrenko

Dulfan

2019

EUREKA: Physics and Engineering

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The study of the temperature field of the engine for non-stationary modes is done. A numerical simulation of a non-stationary thermal process using dynamic EHD, the characteristic of the rate of rise of temperatures is done. An increase in the temperature of individual parts in the idle interval, when the power of heat release is significantly reduced, is established, and the reverse of the heat flow through the air gap is established. It is shown that the EHD method, in contrast to the FEM, is self-sufficient, which determines its practical value. In various parts of the speed control range in the implementation of various laws of regulation. At the same time, the main electrical, magnetic and additional losses associated with the fundamental voltage harmonics (FVH), and mechanical losses, as well as additional electrical and magnetic losses associated with the higher voltage harmonics, change. When using serial asynchronous engines as frequency-controlled. Permissible under the conditions of heating power is significantly reduced by the power of serial engines. Depending on the synchronous speed, the reduction is from 10 % to 20 %. Given the additional overheating due to higher voltage harmonics, as well as the deterioration of the cooling conditions when adjusting the rotational speed "down" from the nominal, it seems very relevant.

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“…When a motor begins to indicate a malfunction, certain changes in operation can become apparent, such as operating temperature (Garcia-Ramirez et al 2014b), mechanical vibrations (Bayram andŞeker 2015), audible noise (GarciaPerez et al 2012), electromagnetic field (Sprooten and Maun 2009) and line current (Roshanfekr and Jalilian 2015;D'Angelo et al 2014). The interpretation of these behavioral changes can be used to detect faults which are still evolving.…”

Section: Introductionmentioning

confidence: 99%

Bearing fault identification of three-phase induction motors bases on two current sensor strategy

et al. 2016

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Three-phase induction motors are the most commonly used devices for electromechanical energy conversion. This study proposes an alternative approach for identifying bearing faults in induction motors, using two current sensors and a pattern classifier, based on artificial neural networks. To validate the methodology, results are given from experiments carried out on a test bench where the motors operate with different types of bearing faults, under varying conditions of load torque and voltage unbalance. This paper also provides the comparative performance of neural network and random forest classifiers. This study also presents an analysis of the current signals in the time domain, applied to different neural structures.

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Fault detection in induction motors and the impact on the kinematic chain through thermographic analysis

Cited by 84 publications

References 29 publications

A comprehensive evaluation of intelligent classifiers for fault identification in three-phase induction motors

A comprehensive evaluation of intelligent classifiers for fault identification in three-phase induction motors

Investigation of the Heating Processes and Temperature Field of the Frequency-Controlled Asynchronous Engine Based on Mathematical Models

Bearing fault identification of three-phase induction motors bases on two current sensor strategy

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