Intelligent Management of Helicopter Health and Usage Management Systems Data

Abstract

Helicopter health and usage management systems (HUMS) generate large amounts of data, which are downloaded to ground-based systems. The data are automatically examined on download for damage indications, which provide the immediate go/no-go response required by the aircraft operations management. This level of reactive fault detection and diagnosis is reasonably well understood and has been demonstrated to improve aircraft availability and airworthiness. To achieve further benefit and maintenance cost savings from HUMS, another level of analysis is required, leading to prognostics and predictive maintenance through intelligent management (IM) of the accumulated HUMS records. In collaboration with the Civil Aviation Authority (CAA), Smiths has developed a suite of IM methods and has successfully applied them to gearbox seeded fault data. Working closely with the UK Ministry of Defence (UK MOD), Smiths has tested these methods on Chinook HUMS data, including an in-flight transmission bearing failure incident described in this article. The result is a high degree of early anomaly detection and a clear view of the deterioration to failure. The objective of the MOD programme has been to apply IM tools to the enormous quantity of HUMS data being gathered, thereby enabling improved analysis capability, increased levels of automation, and more intelligent use of resources. The article presents the results of the work carried out under both the CAA and the MOD programmes.