From Large Time Series to Patterns Movies: Application to Airbus Helicopters Flight Data

Abstract

Huge amount of multivariate time series (TS) data are recorded by helicopters in operation, such as oil temperature, oil pressure, altitude, rotor speed to mention a few. Despite the effort deployed by Airbus Helicopters towards an effective use of those TS data, getting meaningful and intuitive representations of them is a never ending process, especially for domain experts who have a limited time budget to get the main insights delivered by data scientists. In this paper, we introduce a simple yet powerful and scalable technique for visualizing large amount of TS data through patterns movies. We borrow the co-occurrence matrix concept from image processing, to create 2D pictures, seen as patterns, from any multivariate TS according to two dimensions over a given period of time. The cascade of such patterns over time produces so-called patterns movies, offering in a few seconds a visualisation of helicopter' parameters in operation over a long period of time, typically one year. We have implemented and conducted experiments on Airbus Helicopters flight data. First outcomes of domain experts on patterns movies are presented.