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Erschienen in:
Preliminary Correlations for Characterizing the Morphology of Abdominal Aortic Aneurysms as Predictor of Rupture Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

4. Diagnosing Time-Dependent Incipient Faults

verfasst von : Lı́dice Camps-Echevarrı́a, Orestes Llanes-Santiago, Haroldo Fraga de Campos Velho, Antônio José da Silva Neto

Erschienen in: Mathematical Modeling and Computational Intelligence in Engineering Applications

Verlag: Springer International Publishing

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Abstract

This chapter focuses on a formulation for fault diagnosis (FDI) using an inverse problem methodology. It has been shown that this approach allows for diagnoses with adequate balance between robustness and sensitivity. The main contribution of this chapter is the expansion of this approach to include the diagnosis of time-dependent incipient faults. The FDI inverse problem is formulated as an optimization problem that is then solved with two metaheuristics: Differential Evolution and its variation Differential Evolution with Particle Collision. The proposed methodology is tested using simulated data from the Two Tanks system, which is recognized as benchmark for control and diagnosis. The results indicate that this proposal is suitable for the aforementioned diagnosis.

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Vorheriges Kapitel Fault Diagnosis with Missing Data Based on Hopfield Neural Networks
Nächstes Kapitel An Indirect Kernel Optimization Approach to Fault Detection with KPCA
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Metadaten
Titel
Diagnosing Time-Dependent Incipient Faults
verfasst von
Lı́dice Camps-Echevarrı́a
Orestes Llanes-Santiago
Haroldo Fraga de Campos Velho
Antônio José da Silva Neto
Copyright-Jahr
2016
Buch
Mathematical Modeling and Computational Intelligence in Engineering Applications

Print ISBN: 978-3-319-38868-7

Electronic ISBN: 978-3-319-38869-4

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-38869-4_4

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