VisualBlock-FIR for Fault Detection and Identification:
Application to the DAMADICS Benchmark Problem
Abstract
This paper describes a fault diagnosis system (FDS) for non-linear plants based
on fuzzy logic. The proposed scheme, named VisualBlock-FIR, runs under the
Simulink framework and enables early fault detection and identification.
During fault detection, the FDS should recognize that the plant behavior
is abnormal, and therefore, that the plant is not working properly. During
fault identification, the FDS should conclude which type of failure has occurred.
The enveloping and acceptability measures introduced in VisualBlock-FIR enhance
the robustness of the overall process. The final part of this research shows how
the proposed approach is used for tackling faults of the DAMADICS benchmark.
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Last modified: November 12, 2007 -- © François Cellier