Virtual Flight Data Recorder for Commercial Aircraft

Abstract

This paper presents preliminary results of the development of a virtual flight data recorder (VFDR) for commercial airliners. Federal Aviation Administration (FAA) regulations, currently being revised, mandate the recording of 11 dynamic parameters, not including the control surface deflections. The absence of these data can be critical for crash investigation purposes. This paper proposed the introduction of a VFDR based on a neural network simulator (NNS) and a neural network reconstructor (NNR). The NNS is trained, using flight data for the particular aircraft, to simulate any desired control surface deflections (or any other parameter of interest not recorded by the FDR), minimizing a cost function based on the differences between the available data from the FDR and the output from the NNS. The VFDR scheme has been introduced, tested, and validated with flight data from a Boeing 737-300 with an FDR with extended recording capabilities showing accurate reconstruction of the control surface deflections' time histories. The VFDR can be considered a tool for crash investigations where control surface failures are believed to be a factor.