Early warning and prediction of flight parameter abnormalities for improved system safety assessment

It is widely accepted that human error is a major contributing factor in aircraft accidents. The early detection of a subsystem abnormality that is developing during flight is potentially important, because the extra time before an alert range is reached may improve the crewʹs situation awareness. The flight crew may thus consider and try more options for dealing with the failure situation. Robust numerical algorithms and techniques are proposed for rapid recognition of faulty situations, which have the potential for such early detection. The warning system includes a model-based multi-step ahead predictor, which provides predictive information on some flight critical parameters. A key feature of the proposed techniques is that it takes advantage of the on-board information redundancy, computer technology and graphics displays, uses the already available measurements and hence requires only input–output processing for implementation in on-board computers. This is an important aspect when considering the testability and certificability of the software implementation. The system is tested on a simulated typical landing approach scenario of a civil aircraft using the RCAM benchmark.