Fault diagnosis of nonlinear and large-scale processes using novel modified kernel Fisher discriminant analysis approach

DOI10.1080/00207721.2014.912780zbMath1333.93030OpenAlexW1964400806MaRDI QIDQ2798434

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Publication date: 12 April 2016

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207721.2014.912780

zbMATH Keywords

fault diagnosisfeature selectionkernel Fisher discriminant analysisimproved biogeography-based optimizationkernel parameter optimization

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) Fault detection; testing in circuits and networks (94C12) Large-scale systems (93A15)

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Cites Work

• A real-coded biogeography-based optimization with mutation
• A reformative kernel Fisher discriminant analysis
• A kernel optimization method based on the localized kernel Fisher criterion
• Fault detection and diagnosis of networked control system
• Active fault diagnosis by controller modification
• Fault detection in rotating machinery using kernel-based probability density estimation
• PLS modelling and fault detection on the Tennessee Eastman benchmark
• Non-linear principal components analysis with application to process fault detection

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