RTAPHM

The RTAPHM (“Real Time Analytics, Prognostics and Health Management”) project, a research project funded by the German Federal Ministry of Economics and Energy from the German Aeronautics Research Programme (LuFo V-3), is concerned with the development of a digital platform for automated service provision for Unmanned Aerial Vehicle (UAV) fleets. The exemplary selected use case of service provision is initially intended to represent an organ transport. An organ transport is defined by its time-critical character. This is where both technologies, the use of UAVs and automated service delivery, come into play. Compared to conventional methods (transport via ambulance and airplane, time-critical e.g. due to rush hour traffic and reloading processes), the use of UAV allows a more direct transport of the organ from the start location to the destination. The automated, digital platform is expected to provide a simple end-2-end application, thereby also saving time and, through the intelligent use of the resources of a UAV fleet, increasing the reliability of the service offered. The developed digital platform should be scalable so that it can also be used for other suitable use cases, such as sea rescue.

Involvement of the FSR

The analysis of sequential system data in real time and the associated estimation of the current and future health status of a single UAV can be optimized by aggregating the data within the digital platform. This increases the availability of the service offered on the one hand and reduces costs due to unforeseen maintenance measures on the other. If sudden changes in the state of health occur during the flight, this can be detected by real-time data analysis and appropriate measures can then be taken. In a critical case, this means that the defective UAV has to land for maintenance, but is navigated to a place where another intact UAV from the fleet is available and can ideally complete the mission on time. A milder form of emergency management is an adjustment of the flight strategy in which the damaged component is relieved and the mission can be terminated. In summary, real-time data analysis thus offers the following advantages:

Increased availability

UAVs are assigned to appropriate missions according to their state of health

Reduced costs

Optimized planning of maintenance processes

Better reliability

Better emergency management through the availability of real-time information

With the help of demonstrators, the potential of the automated, digital service platform in relation to different, scalable use cases will be demonstrated. Thus, the project contributes to the overall goal of increasing efficiency and performance within aviation.

The FSR has been engaged in the data-based estimation of the health status of different aircraft components for quite some time. For this purpose, a basic procedure has been developed that can be implemented with the help of algorithms from the fields of machine learning and artificial intelligence. The functionality and advantages of the data-based approach were demonstrated in previous research projects.

The RTAPHM project will provide additional research topics in the field of Prognostics and Health Management:

  • Estimation of the real-time capability of algorithms from the PHM area
  • Assignment of the complexity of different algorithms to available computing capacities
  • Use the results of PHM algorithms as input for an automated decision process at fleet level

The project will be carried out until 2022 in cooperation with the following project partners:

If you have further questions or are interested in writing your thesis, please contact Lorenz Dingeldein.