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and the use of high-caliber cables that do not facilitate the installation
of sensors, to name a few.
Conclusions
Induction motor fault detection has been a topic of discussion
for the past few decades. Contributions in this area are made
in instrumentation systems, signal processing algorithms, and
processing systems. With an industry that is improving and
adapting to new technologies, the monitoring and maintenance
of electrical machines must be adjusted at the same pace. With
the advance in electronics, the demand for more efficient detection
algorithms is growing. Currently, the aim is to detect
incipient damage, make prognoses and detect multiple faults
using the same system with an acceptable level of precision and
accuracy, in addition to seeking real-time and online implementations
that allow the systematic programming of prevention
actions, without the need to stop the production process. Moreover,
it should meet the current requirements of the industry 4.0.
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José de Jesús Rangel-Magdaleno (S'08-M'13-SM'17) (jrangel@
inaoep.mx) is Full Researcher at the Electronics Department at
the National Institute of Astrophysics, Optics and Electronics,
(INAOE), Tonantzintla, Puebla, Mexico. His research interests
include FPGAs, signal and image processing, instrumentation
and mechatronics. He received the B.E. degree in electronics
engineering and the M.E. degree in electrical engineering on
hardware signal processing from Universidad de Guanajuato,
Mexico in 2006 and 2008, respectively. He received the Ph.D.
degree from the Autonomous University of Querétaro, Mexico
in 2011. Dr. Rangel-Magdaleno received the 2018 IEEE Instrumentation
and Measurement Society's Outstanding Young
Engineer Award. He is a member of the Mexican national research
system (SNI), level 2.
October 2021
IEEE Instrumentation & Measurement Magazine
71
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