Expert systems for real-time monitoring and fault diagnosis

Methods for building real-time onboard expert systems were investigated, and the use of expert systems technology was demonstrated in improving the performance of current real-time onboard monitoring and fault diagnosis applications. The potential applications of the proposed research include an expert system environment allowing the integration of expert systems into conventional time-critical application solutions, a grammar for describing the discrete event behavior of monitoring and fault diagnosis systems, and their applications to new real-time hardware fault diagnosis and monitoring systems for aircraft.

[1]  Michael Palmer,et al.  An evaluation of a real-time fault diagnosis expert system for aircraft applications , 1987, 26th IEEE Conference on Decision and Control.

[2]  Paul C. Schutte,et al.  Implementation of a research prototype onboard fault monitoring and diagnosis system , 1987 .

[3]  K. Davis.  Diagnostic expert system for the B1B , 1988, IEEE Aerospace and Electronic Systems Magazine.

[4]  Kenneth D. Forbus.  Interpreting Observations of Physical Systems , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  Bruce G. Buchanan,et al.  Dendral and Meta-Dendral: Their Applications Dimension , 1978, Artif. Intell..

[6]  John G Malcolm,et al.  Analysis of Built-in-Test (BIT) False Alarm Conditions , 1981 .

[7]  Charles L. Forgy,et al.  Rete: a fast algorithm for the many pattern/many object pattern match problem , 1991 .

[8]  T. Govindaraj.  Qualitative approximation methodology for modeling and simulation of large dynamic systems: Applications to a marine steam power plant , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[9]  A Gupta,et al.  Parallelism in production systems: the sources and the unexpected speed up , 1986 .

[10]  Kenneth D. Forbus.  Qualitative Process Theory , 1984, Artif. Intell..

[11]  N. Lance,et al.  Processes in construction of failure management expert systems from device design information , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[12]  Randall Davis,et al.  Reasoning from First Principles in Electronic Troubleshooting , 1983, Int. J. Man Mach. Stud..

[13]  Kenneth D. Forbus.  Qualitative physics: past present and future , 1988 .

[14]  Eugene L. Duke,et al.  Development of a knowledge acquisition tool for an expert system flight status monitor , 1986 .

[15]  Thomas J. Laffey,et al.  Real-Time Knowledge-Based Systems , 1988, AI Mag..

[16]  Charles L. Forgy,et al.  Rete: A Fast Algorithm for the Many Patterns/Many Objects Match Problem , 1982, Artif. Intell..

[17]  V. A. Regenie,et al.  Design of an expert-system flight status monitor , 1985 .

[18]  Y. Shoham.  Reasoning About Change: Time and Causation from the Standpoint of Artificial Intelligence , 1987 .

[19]  Jens Rasmussen,et al.  The role of hierarchical knowledge representation in decisionmaking and system management , 1985, IEEE Transactions on Systems, Man, and Cybernetics.