Authors:
Haris M. Khalid
1
;
Rajamani Doraiswami
2
and
Lahouari Cheded
1
Affiliations:
1
King Fahd University of Petroleum and Minerals, Saudi Arabia
;
2
University of New Brunswick, Canada
Keyword(s):
Incipient faults, Holistic approach, Fault diagnosis, Model based, Integrated approach.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Decision Support Systems
;
Enterprise Information Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Intelligent Fault Detection and Identification
;
Knowledge-Based Systems Applications
Abstract:
An intelligent diagnostic scheme using sensor network for incipient faults is proposed using a holistic approach which integrates model-, fuzzy logic-, neural network- based schemes. In case the system is highly non-linear and there are enough training data available, a neural network based scheme is preferred; where the rules relating the input and output can be derived, a Fuzzy-logic approach is chosen; and where a model is available, a linearized model is employed. These three schemes are integrated sequentially ensuring thereby that critical information about the presence or absence of a fault is monitored in the shortest possible time, and the complete status regarding the fault is unfolded in time. The proposed scheme is evaluated extensively on simulated examples and on a physical system exemplified by a benchmarked laboratory-scale two-tank system to detect and isolate faults including sensor, actuator and leakage ones.