Computing environment system for monitoring aircraft engines

A computing environment system for monitoring aircraft engines, said system being connected to a cluster of servers, wherein said system comprises:

• processing circuitry configured to
• receive user codes deployed in the server cluster and including specifications of input and output data, said user codes specifying the calculation of a set of indicators representing the health state of an aircraft engine for deployment on a fleet of aircraft engines, the user codes include specifications of input data to be processed in parallel and output data comprising context and health indicators, said user codes being described in at least two different languages chosen from parallel languages of the Spark type as well as business languages of the Scala, Python, or R type,
• extract, by an application programming interface (API), said indicators by deploying parallel calculations in the server cluster on temporal flight data from the fleet of aircraft engines and stored in a database distributed over said cluster of servers, such that the API is configured to (i) encapsulate the user codes to cause the user codes to operate identically in different data domains and (ii) automatically deploy the user codes a distributed manner over said cluster of servers,
• use said indicators to construct, without supervision, from said indicators, a monitoring model representative of the indicators by implementing predetermined learning functions, wherein the indicators are filtered and ranked on a map, and the monitoring model maps the indicators relative to states of the engines independently of the context, to rank the engines according to similar behaviours, and
• display a visual representation of the monitoring model,
• wherein the temporal flight data is continuous operating data of the engine from sensors and computers associated with the aircraft engines as well as continuous data from aircraft, said temporal flight data being stored in a system of files distributed over said cluster of servers, and
• the processing circuitry is configured to form the temporal vectors by aggregating said temporal flight data on new incoming data flight by flight without requiring processing of a data line of the temporal flight data per step of time.