Instrumentation & Measurement Magazine 24-3 - 3

guesteditorial
Shervin Shirmohammadi

Instrumentation and Measurement in Canada, Part B

P

art A of this Special Issue (SI) on Instrumentation and
Measurement in Canada was presented in the April
2021 Issue. Here, we continue the SI in Part B, starting
with the topic of Measurement Fundamentals which opens
with three articles from Canada's National Research Council (NRC). It's not surprising to see three articles from NRC,
considering that it comprises Canada's various metrology,
standards, and calibration laboratories, centers, and services.
In the first NRC article, " Realizing the Kilogram from the
Planck Constant: The Kibble Balance and the Electrical Units, "
Sanchez gives simplified answers to complicated questions
that arise from the recent redefinition of the international System of Units (SI) which abandoned the artifact definition of the
kilogram in favor of fixing the numerical value of the Planck
constant: how do we understand the link between the kilogram and the Planck constant? And how can we realize the
kilogram now, using the new definition?
The second NRC article is " Measurement of Voltage, Current and Power at Distorted Waveforms " by Djokic´ and Parks
that describes the calibrations of high-voltage and high-current transformers and recent developments in the calibration
of power instrumentation at NRC, undertaken to increase the
frequency range and accuracy of harmonics calibrations at
higher frequencies. This is important because harmonics have
to be monitored and controlled according to national and international standards due to their negative effects.
The last article from NRC is by Kuerten Ihlenfeld who, in
" Digital Sampling Techniques for AC Josephson Standards at
NRC - Canada, " describes the work being conducted at NRC
in the field of AC metrology aiming at establishing a Josephson
based system to provide traceability to the SI for measurements of low frequency ac quantities via digital sampling
techniques. The article suggests that measurement uncertainties bearing parts in 107 or much less for frequencies up to 1
kHz are attainable.
Continuing with the topic of measurement fundamentals, my co-author Al Osman and I present " Machine Learning
in Measurement Part 2: Uncertainty Quantification, " which
continues from Part 1 published in the April 2021 Issue and
describes how to quantify the uncertainty of ML, specifically
Deep Learning, when used as part of a measurement instrument. Expressing uncertainty has become crucial for the

May 2021	

adoption of ML in commercial products and services because
products that specify their uncertainty can have a significant
competitive advantage and can unlock new value, reduce risk,
and improve usability.
The final article in this topic is " A Modern Solution for an
Old Calibration Problem " by Qiu et al. from Western University, who review some of the classic methods proposed in the
literature for the hand-eye calibration problem as well as those
for point set matching, and explain how the problem of handeye calibration with the employment of stereo cameras can
be formulated and solved as a point-set-matching problem to
gain better calibration accuracy. Experiments show that pointset-matching methods outperform the conventional hand-eye
calibration methods.
We then move to the topic of Sensing and Monitoring,
starting with " The Potential of Digital Twins " by El Saddik
et al. from University of Ottawa. Here we learn about Digital
Twin technology which is already proven to be very beneficial in industrial processes and has gained wide adoption by
companies worldwide, affecting smart cities for the benefit of
citizens, health and well-being, social interactions, sports, and
memory improvements. The article also discusses challenges
that have yet to be solved.
The next article is " Analysis of Fault Detection in Rolling
Element Bearings " by Wang from Lakehead University, who
brings us up to date on recent developments in bearing fault
detection and the challenges facing reliable bearing health condition monitoring, discussing bearing characteristic frequency
analysis, denoising to improve the signal-to-noise ratio, and
advanced signal processing techniques for nonstationary signal analysis and bearing fault detection. This is important
because most machinery imperfections are related to bearing
defects, so reliable bearing fault detection techniques are crucial for predictive maintenance operations.
In " RFID Sensing Technologies for Smart Agriculture, "
Rayhana et al. from University of British Columbia and
NRC introduce RFID sensing technology, then survey its
applications to the four areas of agriculture: plant growing environment, soil conditions, plant growth, and the quality of the
harvests. They identify the uniqueness of RFID sensing technology in solving agriculture issues and its limitations. This
contributes to Smart Agriculture which aims to automate most

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