Memoirs of the Faculty of Engineering, Okayama University
Published by Faculty of Enginerring, Okayama University

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Memoirs of the School of Engineering, Okayama University

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Process Fault Diagnosis using Neural Networks and Fault Tree Analysis Information

島田 行恭 Department of Mechanical Engineering
鈴木 和彦 Department of Mechanical Engineering
佐山 隼敏 Department of Mechanical Engineering
Neural nets have recently become the focus of much attention, largely because of their wide range of complex and nonlinear problems. This paper presents a new integrated approach using neural networks for diagnosing process failures. The fault propagation in process is modeled by causal relationships from the fault tree and its minimal cut sets. The measurement patterns required for training and testing the neural network were obtained from fault propagation model. The network is able to diagnose even in the presence of malfunction of certain sensors. We demonstrate via a nitric acid cooler process how the neural network can learn and successfully diagnose the faults.