Efficient Plant April 2019 - 22

feature | reliability strategies
Wireless sensors are attached to a liquid-cooled
motor to measure vibration and temperature.
The sensors send information in customizable
intervals to a cloud server where the data is
aggregated, stored, analyzed, and visualized.

hundreds of IoT-enabled motors, depending
on the service provider's capacity and owner/operator's preferences. At whatever scale
is chosen, the goal is the same: to predict
equipment failure before it happens and so
avoid consequential damages.
Unexpected breakdowns not only lead to
costly downtime, but also further damage to
equipment. IoT-enabled technologies help
maximize equipment life without increasing
failure risks. It not only identifies the best
time for maintenance, but also the scope of

22

| EFFICIENTPLANTMAG.COM

work that should be performed.
Demand for continuous condition
monitoring is increasing among small- and
medium-sized enterprises. Sensors, processing power, communication capabilities, and
data-storage costs have dropped dramatically in the past few years. This has put IoT
technologies within reach for many more
industrial monitoring and control-system
applications than thought possible two or
three years ago. The situation has great significance for a site's electric-motor fleet.

Advances in reliable, automated wireless
sensors have led to affordable multifunctional, wireless monitoring. Once collected,
data is processed and put in some form of
graph or chart, then personnel can begin to
determine the equipment's current health.
The plant operator can trend these critical
parameters and set thresholds for earlier
warning, in real time.
Although this is a good format to monitor critical parameters and react as they
move out of acceptable ranges, the ultimate
process monitoring and evaluation uses
predictive analytics. Predictive analytics
adds a more sophisticated approach to
this monitoring, to gain even more value
and address issues that may arise. In this
approach, algorithms learn, model, and
identify patterns of the rotating equipment,
not just the process limits. This provides the
ability to trend individual processes over
time and determine a course of action.
With predictive analytics and the use of
wireless sensors, the trending process can
be adjusted for the machine operation and
determine patterns for early detection and
protection. By adding such analytics, a site
can create a true PdM system. As operations
transition toward continuous real-time
monitoring of motor health, the number of
IoT-equipped motors will continue to grow.
So will the operating efficiency and productivity of the plants these fleets serve. EP
Jim Sanderson is a division electrical engineer at Motion Industries, Birmingham, AL.
Thomas Schardt is senior director of IoT for
Nidec Motor Corp., St. Louis. Visit MotionIndustries.com/efficientplant and TheMotorSpecialist.com.

APRIL 2019


http://www.motionIndustries.com/efficientplant http://www.TheMotorSpecialist.com http://www.EFFICIENTPLANTMAG.COM

Efficient Plant April 2019

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