PROPOSAL NUMBER 00-1 01.04-8944 (Chron: 001057 )
Aircraft Prognostics and Health Management, and Adaptive Reconfigurable Control

Scientific Systems Company Inc. (SSCI) proposes to develop
nonlinear on-line Health Monitoring (HM), Failure Detection and
Identification (FDI) and Adaptive Reconfigurable Control (ARC)
algorithms for the case of failures of Electro-Mechanical Actuators
(EMAs) and other subsystems and components of a modern combat
aircraft. The proposed algorithms will result in fast and accurate
on-line FDI and ARC for EMAs whose behavior is characterized by
highly nonlinear dynamics. The proposed on-line HM-FDI and ARC
scheme will be integrated into Boeing's open Prognostics and Health
Management (PHM) and Open Control Platform (OCP)
architectures. In order to achieve the above objectives, we propose to
carry out in Phase I the following tasks: (i) Formulation of the
HM-FDI and ARC problem for Electro-Mechanical Actuators
(EMAs). (ii) Acquisition of nonlinear actuator models from Boeing.
(iii) Development of on-line nonlinear HM-FDI and ARC
algorithms compatible with the PHM and OCP architectures for the
nonlinear actuator models. (iv) Testing, tuning and performance
evaluation of the algorithms on a linearized TAFA simulation. (v)
Integration of the HM-FDI and ARC algorithms into the PHM and
OCP. In Phase II we plan to integrate our HM-FDI and ARC
algorithms into Boeing's PMH and OCP systems and test them under
laboratory conditions at Boeing, and in flight tests. The end product
of this research will be a user-friendly software design toolkit for
on-line HM-FDI and ARC. Boeing Phantom Works will provide
technical and commercialization support in all phases of the project.

Recent analyses carried out by Boeing have revealed that decrease in
Can-Not-Duplicate (CND) failures and false alarms by 50% on a
platform such as the C-17 or F/A-18, would result in a maintenance
cost savings of over $100M over the life of the aircraft. The approach
pursued by Boeing is based on predictive diagnostics, or prognostics,
combined with on-line FDI algorithms and data mining techniques,
and will be used to identify more accurately the root causes of failures.
Such an approach has a potential to achieve substantial decrease in
CND failures and false alarms. The resulting architecture, under
development by Boeing, is referred to as the open Prognostics and
Health Management (PHM) system, and is expected to result in a
substantial decrease in operational maintenance costs for modern
aircraft. Efficient ARC algorithms are an important component of
the future Vehicle Management Systems (VMSs) for modern aircraft.
Hence the proposed HM-FDI and ARC algorithms, that will be an
integral part of the PMH and the aircraft Operational Maintenance
Program (OMP), have a great commercial potential in the area of
operational maintenance and safety improvements in modern

NAME AND ADDRESS OF PRINCIPAL INVESTIGATOR (Name, Organization Name, Mail Address, City/State/Zip)
Jovan D. Boskovic
Scientific Systems Company Inc
500 West Cummings Park, Suite 3000
Woburn , MA   01801 - 6580

NAME AND ADDRESS OF OFFEROR (Firm Name, Mail Address, City/State/Zip)
Scientific Systems Company Inc
500 West Cummings Park, Suite 3000
Woburn , MA   01801 - 6580