Paper
26 March 1986 A Flight Expert System (FLES) For On-Board Fault Monitoring And Diagnosis
M. Ali, D. .A Scharnhorst, C. S. Ai, H. J. Ferber
Author Affiliations +
Proceedings Volume 0635, Applications of Artificial Intelligence III; (1986) https://doi.org/10.1117/12.964111
Event: 1986 Technical Symposium Southeast, 1986, Orlando, United States
Abstract
The increasing complexity of modern aircraft creates a need for a larger number of caution and warning devices. But more alerts require more memorization and higher work loads for the pilot and tend to induce a higher probability of errors. Therefore, we have developed an architecture for a flight expert system (FLES) to assist pilots in monitoring, diagnosing and recovering from in-flight faults. A prototype of FLES has been implemented. A sensor simulation model was developed and employed to provide FLES with the airplane status information during the diagnostic process. The simulator is based partly on the Lockheed Advanced Concept System (ACS), a future generation airplane, and partly on the Boeing 737, an existing airplane. A distinction between two types of faults, maladjustments and malfunctions, has led us to take two approaches to fault diagnosis. These approaches are evident in two FLES subsystems: the flight phase monitor and the sensor interrupt handler. The specific problem addressed in these subsystems has been that of integrating information received from multiple sensors with domain knowledge in order to assess abnormal situations during airplane flight. This paper describes our reasons for handling malfunctions and maladjustments separately and the use of domain knowledge in the diagnosis of each.
© (1986) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Ali, D. .A Scharnhorst, C. S. Ai, and H. J. Ferber "A Flight Expert System (FLES) For On-Board Fault Monitoring And Diagnosis", Proc. SPIE 0635, Applications of Artificial Intelligence III, (26 March 1986); https://doi.org/10.1117/12.964111
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Cited by 7 scholarly publications.
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KEYWORDS
Sensors

Diagnostics

Control systems

Prototyping

Artificial intelligence

Computer simulations

Mechanics

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