Employing Agent Beliefs during Fault Diagnosis for IEC 61499 Industrial Cyber-Physical Systems
This work addresses fault identification for industrial cyber-physical systems, but it appears incremental as it focuses on implementing specific belief structures within an existing framework.
The paper tackles fault diagnosis in IEC 61499 industrial cyber-physical systems by employing software agents that use domain knowledge to build and refine beliefs about faults, demonstrating three belief structures within a Fault Diagnostic Engine to support agent reasoning.
We have come to rely on industrial-scale cyber-physical systems more and more to manage tasks and machinery in safety-critical situations. Efficient, reliable fault identification and management has become a critical factor in the design of these increasingly sophisticated and complex devices. Teams of co-operating software agents are one way to coordinate the flow of diagnostic information gathered during fault-finding. By wielding domain knowledge of the software architecture used to construct the system, agents build and refine their beliefs about the location and root cause of faults. This paper examines how agents constructed within the GORITE Multi-Agent Framework create and refine their beliefs. We demonstrate three different belief structures implemented within our Fault Diagnostic Engine, showing how each supports a distinct aspect of the agent's reasoning. Using domain knowledge of the IEC 61499 Function Block architecture, agents are able to examine and rigorously evaluate both individual components and entire subsystems.