Detecting faults in heterogeneous and dynamic systems using DSP and an agent-based architecture

Authors:
Osama Zaki;Keith Brown;John Fletcher;David Lane
Affiliations:
Electrical, Electronic and Computer Engineering, Heriot-Watt University, Edinburgh, Scotland, UK;Electrical, Electronic and Computer Engineering, Heriot-Watt University, Edinburgh, Scotland, UK;Electrical, Electronic and Computer Engineering, Heriot-Watt University, Edinburgh, Scotland, UK;Electrical, Electronic and Computer Engineering, Heriot-Watt University, Edinburgh, Scotland, UK
Venue:
Engineering Applications of Artificial Intelligence
Year:
2007

Citing 2
Cited 4

An analysis of multi-agent diagnosis

Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
Real time automated diagnosis using matrix failure modes and effects analysis

IEA/AIE'93 Proceedings of the 6th international conference on Industrial and engineering applications of artificial intelligence and expert systems

Dynamic independent component analysis approach for fault detection and diagnosis

Expert Systems with Applications: An International Journal
Embedded holonic fault diagnosis of complex transportation systems

Engineering Applications of Artificial Intelligence
Multi-BP expert system for fault diagnosis of powersystem

Engineering Applications of Artificial Intelligence
Increasing mapping based hidden Markov model for dynamic process monitoring and diagnosis

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper demonstrates the use of multi-agent systems (MAS), firstly as a modelling technique for dynamic physical systems and secondly as the basis for a generic and powerful diagnostic system, which can support heterogeneous distributed systems. First an overview of the diagnostic techniques including those offered by the two communities fault detection and isolation (FDI ) and DX (based on intelligent techniques) is given. The use of digital signal processing (DSP) as a significant technique for improved fault diagnosis is illustrated. A rule-based engine is used to control the behaviours of the agents and also as a tool for diagnosis. Finally, the integration of DSP agents and the rule-based engine into MAS is demonstrated using a real-life application, a class-AB amplifier (a power electronic circuit). It is shown that the integration of DSP agents and rules into MAS provides a powerful tool for prognosis and for detection of abrupt (short and open circuit) and incipient faults.