Article
The Use of Digital Twins in Finite Element for the Study of
Induction Motors Faults
Tiago Drummond Lopes
1,2,
* , Adroaldo Raizer
2
and Wilson Valente Júnior
1
Citation: Lopes, T.D.; Raizer, A.;
Valente Júnior, W. The Use of Digital
Twins in Finite Element for the Study
of Induction Motors Faults. Sensors
2021, 21, 7833. https://doi.org/
10.3390/ s21237833
Academic Editors: Hamed Badihi,
Tao Chen and Ningyun Lu
Received: 9 October 2021
Accepted: 22 November 2021
Published: 25 November 2021
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affil-
iations.
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1
Department of Electrical Engineering, Federal Institute of Santa Catarina, Av. Ver. Abrahão João Francisco,
3899, Itajaí 88307-303, Brazil; wilson.valente@ifsc.edu.br
2
Department of Electrical Engineering, Federal University of Santa Catarina, R. Roberto Sampaio Gonzaga,
s/n, Florianópolis 88040-900, Brazil; raizer@eel.ufsc.br
* Correspondence: tiago.drummond@ifsc.edu.br
Abstract:
Induction motors play a key role in the industrial sector. Thus, the correct diagnosis and
classification of faults on these machines are important, even in the initial stages of evolution. Such
analysis allows for increased productivity, avoids unexpected process interruptions, and prevents
damage to machines. Usually, fault diagnosis is carried out by analyzing the characteristic effects
caused by the faults. Thus, it is necessary to know and understand the behavior during the operation
of the faulty machine. In general, monitoring these characteristics is complex, as it is necessary to
acquire signals from the same motor with and without failures for comparison purposes. Whether
in an industrial environment or in laboratories, the experimental characterization of failures can
become unfeasible for several reasons. Thus, computer simulation of faulty motors digital twins can
be an important alternative for failure analysis, especially in large motors. From this perspective,
this paper presents and discusses several limitations found in the technical literature that can be
minimized with the implementation of digital twins. In addition, a 3D finite element model of an
induction motor with broken rotor bars is demonstrated, and motor current signature analysis is
used to verify the fault effects. Results are analyzed in the time and frequency domain. Additionally,
an artificial neural network of the multilayer perceptron type is used to classify the failure of broken
bars in the 3D model rotor.
Keywords:
condition monitoring; digital twin; fault diagnosis; finite element method; non-destructive
testing methods; simulation 3D models; three-phase induction motor
1. Introduction
Among all types of electric motors available on the market, the most popular is
the three-phase induction [
1
,
2
]. After all, this equipment stands out compared to others
for having characteristics such as: high efficiency, simple construction, robustness, high
starting torque, low maintenance, and convenient power–volume ratio [3]. It is estimated
that around 40% of the world electricity production is consumed by these machines, which
are the largest energy consumers in the industrial sector (80%) [4,5].
Thus, three-phase induction motors (TIM) are considered reliable equipment that do
not fail frequently. However, it commonly operates exposed to unfavorable environmental
conditions, such as the presence of humidity and dust. Still other factors, such as power
quality problems and mechanical overload, corroborate the faults appearance in these
motors [6].
Incipient faults at TIM can be originated mechanically or electrically. Faults considered
mechanical are responsible for approximately 40% to 50% of the operation interruption and
are generally related to bearings, bearing wear, or still eccentricity [
7
]. The most common
electrical faults are problems in the stator winding, which represent about 37% of faults in
TIM, and the rotor bars breakage, which accounts for 10% of these occurrences [
8
]. These
Sensors 2021, 21, 7833. https://doi.org/10.3390/s21237833 https://www.mdpi.com/journal/sensors
