The paper provides further details of the automated failure modes and effects analysis (FMEA) program outlined in Part 1. Some of the more dijj'jcult development problems are discussed, and solutions are presented. The ,functionality of the program was tested through application to two experimental rigs, namely a closed-loop hydrostatic transmission with a dynamometer and a regenerative pump test rig. Non-destructive faults, such as abnormally low relief valve settings and excessive loads, were manually inserted into these rigs, und the measured Cfects were compared with the predictions from the program lo validale the software. The diference in complexity and contigurution evident in the two examples considered serves to highlight the generality of the approach. The ease ofreconj5gurability oj the software reflects the key aim of producing a program capable of analysing a wide range of hydraulic circuits.
Early expert systems for fault analysis tended to be based on shallow, heuristic knowledge. For success in engineering applications, it is argued that the complementary knowledge of the underlying principles (deep knowledge) should also be modelled. An object-oriented software library representing models of components of hydraulic circuits is being built using deep knowledge alone. The software modules within this library are reusable for the construction of model-based expert systems for the performance of failure mode and effects analysis and fault tree analysis on any arbitrary hydraulic circuit.
When a fault occurs in a power system, the protective relays detect the fault and trip appropriate circuit breakers, which isolate the affected equipment from the rest of the power system. Fault diagnosis of power systems is the process of identifying faulty components and/or sections by analysing observable symptoms (telemetry messages). As the domain itself is characterised by dynamic situations, extensive telemetering, complex operations, and distribution of lines and substations over a large geographical area, it is difficult to tackle fault diagnosis problems through the strength and capability of a single intelligent system. This paper describes an experimental multi-agent system developed for and aimed at a computer-supported fault diagnosis in electricity distribution networks. The system is based on a hierarchy of five agents that cooperate with each other to diagnose a fault. The results obtained suggest that agent-based approach is very efficient and with a good potential for real-time application.
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