Advances in Fault Detection and Diagnosis Using Filtering Analysis

The book provides fault detection and diagnosis approaches from the perspective of filtering analysis,using set-membership principles to deal with unknown but bounded noise terms. It covers typical application cases and is valuable for students, teachers, engineers, and researchers in the field.

Format: Paperback / softback
Length: 176 pages
Publication date: 27 October 2022
Publisher: Springer Verlag, Singapore

The book delves into fault detection and diagnosis methodologies, employing filtering analysis as a framework. It employs set-membership principles to handle the enigmatic yet bounded noise term, enabling the design of fault detection filters. Various regular geometric spaces, including ellipsoids, polyhedrons, and intervals, are introduced to describe the feasible parameter sets of the given system. A balanced approach between principles and engineering practice is taken, with a greater emphasis on practical applications. Thorough case studies are presented, examining fault detection and diagnosis in diverse fields such as power converters, permanent magnet synchronous motors, and wind turbine pitch systems. Given its comprehensive coverage, the book serves as a valuable resource for students, teachers, engineers, and researchers engaged in the realm of fault detection and diagnosis.

Weight: 314g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811659614
Edition number: 1st ed. 2022