Artificial intelligence and big data analysis promise a better way to operate and maintain aircraft and engines, we are often told. Yet it is sometimes overlooked that no matter how smart the algorithm, its output will always depend on the quality of the information it receives.
In medical technology, for example, the precision of the measuring hardware is obviously crucial. How data is transmitted is also significant: even the most advanced 5G networks are not quick enough to enable large-scale networks of driverless cars without significant computing power in the car itself (and not in the cloud).
Similar concerns apply to aviation, in particular the data that is applied to predictive maintenance and lifecycle analysis of engines.
“Faster response times and accuracies directly facilitate improved, or more responsive controls and also allow monitoring systems to better evaluate system health,” Scott Wright, a chief consulting engineer at GE Aviation, tells Engine Yearbook.
All engine OEMs are investing in sensor technology, improvements of which include plug-and-play devices – self-powered devices that could be plugged in at a later stage in an engine’s life and connected to the engine management unit (EMU) to record new parameters
Meanwhile, increasing satellite communication bandwidth for aircraft has raised the possibility of engine data being streamed to the ground continuously.
However, the volume of raw data is much too large to transmit more than a fraction from the air.
One solution is edge analytics for pre-transmission data processing. On-board the aircraft such software applies its own analytics to work out what data it wants to condense down and put into ACARS or other maintenance messages.
To find out more about the future of engine sensors and data communication from aircraft, see the forthcoming Engine Yearbook 2019.