Data acquisition systems
“CrateDB is extremely fast and highly
scalable,” says Sutterlüti. “That’s why we
use the database to store and access all
aggregated measurement data. Working
with CrateDB demonstrates the potential
that can come from combining edge
computing, big data handling, and
machine learning.”
CONNECTIVITY
Increasingly more test labs use specialised
control, monitoring and data acquisition
systems. Examples in the field have shown
that the lack of integration between these
systems still leads to late detection of
122 SHOWCASE 2020 \\ AEROSPACETESTINGINTERNATIONAL.COM
structural or system anomalies. One of the
reasons is that multi-source and/or
metadata is not readily available during the
test. Measurement data can therefore not
be fully analyzed until the end of the test
run (or at predefined intervals).
The Kafka stream processing engine
comes with an extensive set of APIs to
integrate 3rd party data streams, for
example from a control system. The
primary measurement data can be
enriched with control and simulation data.
Providing an open software architecture
that supports a variety of publishsubscribe
based protocols (like MQTT and
DDS), allows seamless integration with
other monitoring, analysis, and reporting
tools. For test labs that currently maintain
automated test systems application
programing interface (API) provides a
simple way to integrate existing
environments. In turn, they’re able to
leverage the automatic recording, data
storage, plotting, and configuration
management capabilities. Users may
also programmatically access data that’s
stored in the data backend for use with
custom graphics, analytics, and report
generation applications.
Gantner’s philosophy is to provide
customers with open interfaces where they
can store data and send that data wherever
they want. Sutterlüti says, “Our customers
value this option quite a bit because it
relieves them from handling data and how
to store it. Instead, they have easy access to
APIs, and all the existing functions they
are used to are still available.”
RAPID ANALYSIS
Analysis or failure detection differs by
application. Common software and user
interfaces for managing, visualizing,
reporting, or defining dedicated event
rules simplify access and integration. This
approach minimizes the investment cost
for IT and storage infrastructure in the test
lab, whilst maintaining the necessary
computing performance for test-critical
data analysis tasks. For example, to
perform temporal and spatial analysis of
aircraft engines, or to better understand
the mechanical response of an aircraft
structural component, powerful querying
capabilities enable engineers to analyze
large amount of sensor data on-the-fly.
Trend monitoring over the entire life of the
test will quickly signal any significant
change in test article response between
repetitive test conditions.
With an adaptive and scalable data
backend solution, Gantner Instruments is
able to provide a platform which allows
test labs to grasp, monitor, analyze and
react on any physical data in real-time and
regardless of the data volume,
transforming data into insight. \\
Stephan Ploegman is the head of business
development at Gantner Instruments
1 // Caption here xxx
xxxxx xxx xxxxxxx
“The Kafka stream processing
engine comes with an
extensive set of APIs”
3 // An Airbus wing tip
structural test can produce
masses of data for analysis
4 // Safran’s Open Rotor
test rig at Istres, France
3
4
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