Data-Driven Design of Fault Diagnosis Systems Nonlinear Multimode Pr
In many industrial applications early detection and diagnosis of abnormal behavior of the plant is of great importance. During the last decades, the complexity of process plants has been drastically increased, which imposes great challenges in development
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Adel Haghani Abandan Sari
Data-Driven Design of Fault Diagnosis Systems Nonlinear Multimode Processes
Adel Haghani Abandan Sari Rostock, Germany
PhD Thesis, University of Duisburg-Essen, 2013
ISBN 978-3-658-05806-7 DOI 10.1007/978-3-658-05807-4
ISBN 978-3-658-05807-4 (eBook)
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Preface In many industrial applications early detection and diagnosis of abnormal behavior of the plant is of great importance. For decades, model-based methods have been widely used to design fault diagnosis systems. These approaches involve rigorous development of a process model based on first principles. During the last decades, the complexity of process plants has been drastically increased, which imposes great challenges in development of model-based monitoring approaches and it sometimes becomes unrealistic for modern large-scale processes. Alternative to model-based approaches, data-driven methods have been devel
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