AOPA Pilot Magazine - November 2022 - 96

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Highly simplified anomaly detection model with just three features.
The vast majority of those points will
be tightly clustered into a 50-dimensional
" blob " that represents what normal data
looks like for the SR22. The edges of the
blob will be a little fuzzy, and there'll be a
relative handful of points that are obvious
outliers because they fall well outside the
body of the blob.
In the jargon of artificial intelligence
(AI) and machine learning, this 50-dimensional
blob is known as " training data "
and the 50 data elements captured by the
engine monitor are called " features. "
Now, suppose a new SR22 flight gets
uploaded to the system. The software
takes each one-second observation and
plots it in 50-dimensional space to see
where it falls. If it falls inside the blob
then it's probably normal, but if it falls
outside the blob or on its edges, it's probably
anomalous-the further outside the
blob it falls, the more anomalous it's likely
to be. We do this for each of the thousands
of observations in the flight, and if more
than a few observations seem to be anomalous,
we'll flag the flight to be reviewed
by a human analyst.
96
AOPA PILOT / November 2022
Although this is conceptually simple-
at least for those of you who can visualize
a 50-dimensional blob-the devil is in the
details. The mathematics of deriving an
" anomaly score " for each observation and
for the flight as a whole is quite complex.
GADfly does it by using a multi-level neural
network, a process AI geeks call " deep
learning. " We were fortunate to be able to
utilize a neural network machine learning
model developed by Google machine
learning engineer (and GA aircraft owner)
John Sipple. A huge shout-out to Sipple
and Google for open-sourcing the algorithm
and making us aware of it.
GADfly oversimplified
It's hard to visualize a 50-dimensional
blob, but most of us are reasonably adept
at visualizing things in three dimensions.
So, let's look at an oversimplified version
of the anomaly detection model with just
three features instead of 50. For purposes
of this exercise, we'll choose CHT and
EGT for cylinder number 2, plus manifold
pressure. To make this 3D model work a
bit better, we'll normalize CHT2 and
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AOPA Pilot Magazine - November 2022

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