How Marple is used in Aerospace
Data analysis has become a major part of research and development in aerospace systems. Aeroplanes, drones, machines, satellites, ... are able to gather more and more data over the years. They are stuffed with hundreds, if not thousands of sensors. This data is used to improve these systems even further. In this use case we will have a look at data from a flight that took place in 2017 with a Cessna Citation II.
The data was logged using a dSpace logger and eventually converted to a
.csv file. It is a large dataset with around 1GB of data. This data can easily be imported in Marple. Using a preview we can have a quick look at the data and determine how the data is imported.
Marple can handle files up to 4 GB
Once we have imported the data we can start visualising it. We have already prepared a workbook so the data is immediately visualised on screen. Note that we can easily plot various signals of different value ranges.
Marple automatically scales signals with different value ranges
For this use case we will have a closer look at the engines during the flight.
The aeroplane has two jet engines. The fuel flow is indicated by the green and blue line. The yellow and orange line indicate the total fuel used. We can see that the right engine is using more fuel compared to the left engine. We can make a new signal in which we can track the relative difference between the two engines.
Marple can create new signals with math functions
The new signal is focused in this view. We can see that the left engine is about 10% more efficient compared to the right one. Using Marple we can actually calculate the mean between two cursors. In this case we can confirm that on average the difference is 9%.
In this use case we managed to analyse data from a Cessna Citation II. We had a closer look at the jet engines and noticed a difference between left and right engine.
With Marple we were able to
- Quickly import a data file
- Open data in an existing workbook
- See many signals in one view
- Create new signals from the data