|•||Identify information and control needs of aircrew for optimal fault management,|
|•||Identify all relevant information that can be supplied by the best available sensors and signal processors, and then|
|•||Build the intelligent interface system that forges the gap between the information and control needs and the information that can be supplied by sensors and signal processors by applying appropriate information processing technology.|
The key to a successful implementation of mechanical diagnostic capabilities within the aircraft crew-station environment is effectively integrating and presenting the information derived from these sensors in a manner that is timely, useful, and readily interpretable by the aircrew. To accomplish this task, a better understanding of the demands required for aircrew to perform within the aircraft environment is a necessity. In other words, the aircrew interface design problem consists of determining what information to present to the aircrew and how to present it.
In order to determine what information should be presented to the aircrew, it is necessary to establish both what information the aircrew needs and wants and also what information can feasiblely be generated to satisfy their needs/desires. Since essentially none of the currently generated advanced sensor outputs are suitable for aircrew presentation due to the complexity of interpretation required, this process is expected to warrant iterative refinement. As a starting point, it is important to identify the general types of information that the aircrew needs, then try to characterize the kinds of information that can be generated in the identified categories. Next, one must assess the utility to the aircrew of those specific kinds of information, etc. It is assumed that all information that might be presented to the aircrew would have to be generated via some kind of aiding algorithm which would use advanced sensor data as its primary input. Such algorithms could vary from extremely simple ones like current chip detector lights which just indicate that some anomaly has been detected, to very sophisticated algorithms which would tell the aircrew precisely what to do to respond optimally to the detected problem.
Advanced mechanical diagnostic technologies are emerging from the Navy scientific and technology community that soon will allow both advanced ground-based diagnostics and mobile data access and onboard real-time processing of data to accurately determine the health of aircraft mechanical systems (summary reviews of this new technology are available in Stevens, Hall, & Smith, 1996; Parry, 1996; Marsh, 1996, and Nickerson, 1994). Through the use of a combination of sensors, software, and displays, it is now possible to track component wear and fatigue trends, monitor for conditions that indicate impending failure, and alert the aircrew. Furthermore, this tracking and monitoring capability will allow accelerated wear and fatigue trends to be identified, so that the aircraft can be flown within its design parameters.
This new diagnostic technology, sometimes called HUMS (Health and Usage Monitoring Systems), has been used by both UK and Norwegian operators during helicopter ferrying services to North Sea oil platforms. Through implementation of this capability in North Sea operations, improvements in flight safety have been realized ( Chamberlain, 1994). HUMS systems have allowed detailed views of rotor system track