3.7. AXIS OF RESEARCH
than any HUMS, simply by using manual screening of the condition indi-cators. This screening is mainly focused on indicator progression analysis. Automating this process will thus provide a substantial improvement of the HUMS, especially of it involves avoiding aircraft individual thresholds. As indicator progression analysis can be developed without any modi.cation to the airborne segment, this axis of research should have the highest priority.
Data Migration
All .rst generation HUMS were made under the assumption that a given air-craft would be associated with a single ground station. Practice has however shown that HUMS data from a single aircraft can be processed at several ground stations, on the various bases of the operator. This creates obvious data consistency problems, as data from a single aircraft will be fragmented across several ground stations.
Another problem is moving data from the operator to Eurocopter. This is performed through backup tapes sent in the paper mail at more or less regular intervals. The procedure is however too slow to perform the customer has a potential problem. In response to possible detections, information is sent to Eurocopter by emailing indicator plot screenshots. This is cumbersome for the operator, and does not always provide Eurocopter support personnel with all the necessary information.
Developing a model which allows migration of HUMS data between ground stations and between ground stations and Eurocopter should be given high priority. Such a model is vital both to answer the clients day to day data migration needs, as well as to provide Eurocopter with a situation awareness concerning its HUMS equipped .eet. The latter point is vital to any fur-ther development the MARMS / EuroARMS systems, as it helps providing relevant data for research into fault detection algorithms.

3.7 Axis of Research
Based on the improvement potential identi.ed in the previous section, this work follows several axis of research. The suggested improvements are how-ever too numerous to be explored in the context of a single PhD. A decision was therefore made to focus on methods not requiring redesign of the air-borne system. This leaves research into methods for improved processing and interpretation of the condition indicators. Further, a set of measures are proposed to deal with some of the data migration issues.
To reduce data scatter, contextual data correction has been developed both for signals and for indicators. Contextual correction of indicators is aimed at indicators originating from short duration acquisitions, for which contextual variation within the acquisition is unlikely. Contextual correction of signals is aimed at long duration signals, and permits correcting a signal piece vice to compensate for context change throughout the period. The latter method remains theoretic as it can not be implemented and tested on the current generation airborne segment. It was developed none the less, due to its relevance for future use.
　
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