Advances in Fault Detection and Diagnosis Using Filtering Analysis
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Beschreibung
The book provides fault detection and diagnosis approaches from the perspective of filtering analysis. In order to design fault detection filters, it uses set-membership principles to deal with the unknown but bounded noise term. Some regular geometric spaces are introduced, such as the ellipsoid, polyhedron, interval, to describe the feasible parameter sets of the given system. Both principles and engineering practice have been addressed, with more weight placed on engineering practice. Some typical application cases are studied for fault detection and diagnosis in detail, which are power converter, permanent magnet synchronous motor, pitch system of wind turbine. Given its scope, the book offers a valuable guide for students, teachers, engineers and researchers in the field of fault detection and diagnosis.
The book provides fault detection and diagnosis approaches from the perspective of filtering analysis. In order to design fault detection filters, it uses set-membership principles to deal with the unknown but bounded noise term. Some regular geometric spaces are introduced, such as the ellipsoid, polyhedron, interval, to describe the feasible parameter sets of the given system. Both principles and engineering practice have been addressed, with more weight placed on engineering practice. Some typical application cases are studied for fault detection and diagnosis in detail, which are power converter, permanent magnet synchronous motor, pitch system of wind turbine. Given its scope, the book offers a valuable guide for students, teachers, engineers and researchers in the field of fault detection and diagnosis.
Addresses fault detection and fault diagnosis process Studies different geometric spaces in filtering technique Provides in-depth treatment of application cases
Autor*in
Ziyun Wang
Themen in »Advances in Fault Detection and Diagnosis Using Filtering Analysis«
Fault Detection Fault Diagnosis Filtering Technique Set-membership Finite Data Window Polyhedral Cone Interval Filter State Space Kalman Filter Orthotope
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“Many examples are given with explicit calculations, algorithms, tables and an unusually large number of illustrations and diagrams. That furthers the intuitive understanding of the matter and encourages the reader to adapt the methods to his own problems and further develop them.” (Heinrich Hering, zbMATH 1504.94003, 2023)
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