COMMAS (COndition Monitoring Multi-Agent System)

Abstract

The application of intelligent systems for data interpretation and condition monitoring is an advancing field of research. In recent years autonomous intelligent agents and multi-agent systems have gained much attention within different real time applications. The novel idea of COMMAS (COndition Monitoring Multi-Agent System) introduces a hierarchical decentralised multi-agent architecture developed for data interpretation and condition monitoring applications. By definition condition monitoring is concerned with detecting and distinguishing faults occurring in plant that is being monitored [1]; therefore the early diagnosis and identification of faults has a number of benefits (improvement in the plant economy, reduction in operational costs, improving the level of safety etc). A variety of intelligent techniques have been applied in plant monitoring, which resulted in the development of centralised approaches for condition monitoring, e.g., Knowledge Based Systems (KBS) [2], Model Based Reasoning (MBR) Systems [3], Case Based Reasoning (CBR) Systems [4], Artificial Neural Networks (ANN) [5] etc. These approaches tend to be fixed, so they lack flexibility and extensibility. Moving to an agent-based architecture allows simultaneous complex tasks to be performed in real-time; better handling of inaccurate data is achieved and each agent can be independently updated.