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Fault diagnosis system based in agents

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Bibliographic Details
Summary:In this work is proposed a new agent based fault diagnosis system for complex and dynamic processes. The fault diagnosis systems of the future should have present the distribution and complexity of the processes and they must be able to cooperate and communicate with other systems to achieved a satisfactory performance. The fault detection and isolation (FDI) agents proposed here have hybrid architectures based in a horizontal layered architecture. The reactive layer of the FDI agents are based in decomposition wavelet methods for the fault detection and in neural networks for the fault isolation task. The new agent based FDI system is applied to fault diagnosis in a three tank process.
Main Authors:Mendes, Mário J. G. C.
Other Authors:Calado, João Manuel Ferreira; Costa, J. M. G Sá da
Subject:Fault diagnosis Distributed Artificial Intelligence Agents Decomposition methods Neural networks
Year:2007
Country:Portugal
Document type:article
Access type:restricted access
Associated institution:Universidade Politécnica de Lisboa
Language:English
Origin:Repositório Científico da Universidade Politécnica de Lisboa
Description
Summary:In this work is proposed a new agent based fault diagnosis system for complex and dynamic processes. The fault diagnosis systems of the future should have present the distribution and complexity of the processes and they must be able to cooperate and communicate with other systems to achieved a satisfactory performance. The fault detection and isolation (FDI) agents proposed here have hybrid architectures based in a horizontal layered architecture. The reactive layer of the FDI agents are based in decomposition wavelet methods for the fault detection and in neural networks for the fault isolation task. The new agent based FDI system is applied to fault diagnosis in a three tank process.

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