Advances in Fault Detection and Diagnosis Using Filtering Analysis (Hardcover, 1st ed. 2022)

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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Release date:	October 2021
First published:	2022
Authors:	Ziyun Wang • Yan Wang • Zhi-Cheng Ji
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	176
Edition:	1st ed. 2022
ISBN-13:	978-981-16-5958-4
Categories:	Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Professional & Technical > Energy technology & engineering > Electrical engineering > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General
LSN:	981-16-5958-3
Barcode:	9789811659584

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