Frank - Fault Diagnosis in Dynamic Systems Using Analytical and Knowledge-based Redundancy.pdf

Automatica, Vol. 26, No. 3, pp. 459-474, 1990 0005-1098/90 $ +
Printed in Great Britain. Pergamon Press plc
© 1990 International Federation of Automatic Control
Survey Paper
Fault Diagnosis in Dynamic Systems Using
Analytical and Knowledge-based Redundancy
A Survey and Some New Results*
PAUL M. FRANKt
A review of the different concepts of model-based fault detection and
isolation in dynamic processes indicates that the practical application can be
considerably improved by a systematic exploitation of the potentialities of
robust residual generation.
Key Words--Failure detection; fault diagnosis; systems failure and recovery; reliability; sensor
failures; actuator failures; redundancy; robustness; observers; expert systems.
Abstract--The paper reviews the state of the art of fault This paper focuses on fault detection and isolation
detection and isolation in automatic processes using (FDI). In this context, a fault is understood as any
analytical redundancy, and presents some new results. It
outlines the principles and most important techniques of kind of malfunction in the actual dynamic system, the
model-based residual generation using parameter identifica- plant, that leads to an eptable anomaly in the
tion and state estimation methods with emphasis upon the overall system performance. Such malfunctions may
latest attempts to achieve robustness with respect to occur either in the sensors (instruments), or actuators,
modelling errors. A solution to the fundamental problem of
robust fault detection, providing the maximum achievable or in ponents of the process. With respect to
robustness by decoupling the effects of faults from each other the different sectors where the faults can occur, one
and from the effects of modelling errors, is given. This distinguishes between instrument fault detection
approach not pletes the theory but is also of great (IFD), actuator fault detection (AFD),