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Advances in fault detection and diagnosis using filtering analysis

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advances in fault detection and diagnosis using filtering analysisby Ziyun Wang, Yan Wang, Zhicheng Ji.
作者:	Wang, Ziyun.
其他作者:	Wang, Yan.
出版者:	Singapore :Springer Singapore :2022.
面頁冊數:	xxi, 176 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Fault location (Engineering)
電子資源:	https://doi.org/10.1007/978-981-16-5959-1
ISBN:	9789811659591$q(electronic bk.)

Advances in fault detection and diagnosis using filtering analysis
Wang, Ziyun.

Advances in fault detection and diagnosis using filtering analysis[electronic resource] /by Ziyun Wang, Yan Wang, Zhicheng Ji. - Singapore :Springer Singapore :2022. - xxi, 176 p. :ill., digital ;24 cm.

Introduction -- Design of state space based fault diagnosis ﬁlter -- Design of ellipsoid set-membership based fault detection ﬁltering -- Design of polyhedron set-membership based fault detection ﬁlter -- Design of interval set-membership based fault detection ﬁlter -- Design of orthotopic set-membership based fault diagnosis ﬁlter -- Fault diagnosis method based on composite set-membership ﬁlter -- Summary.

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.

ISBN: 9789811659591$q(electronic bk.)

Standard No.: 10.1007/978-981-16-5959-1doiSubjects--Topical Terms:

266155
Fault location (Engineering)

LC Class. No.: TA169.6 / .W36 2022

Dewey Class. No.: 620.0044

Advances in fault detection and diagnosis using filtering analysis
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245 1 0 $a Advances in fault detection and diagnosis using filtering analysis $h [electronic resource] / $c by Ziyun Wang, Yan Wang, Zhicheng Ji.
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300 $a xxi, 176 p. : $b ill., digital ; $c 24 cm.
505 0 $a Introduction -- Design of state space based fault diagnosis ﬁlter -- Design of ellipsoid set-membership based fault detection ﬁltering -- Design of polyhedron set-membership based fault detection ﬁlter -- Design of interval set-membership based fault detection ﬁlter -- Design of orthotopic set-membership based fault diagnosis ﬁlter -- Fault diagnosis method based on composite set-membership ﬁlter -- Summary.
520 $a 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.
650 0 $a Fault location (Engineering) $3 266155
650 0 $a Kalman filtering. $3 213996
650 1 4 $a Control and Systems Theory. $3 825946
650 2 4 $a Mathematical and Computational Engineering. $3 775095
650 2 4 $a Cyber-physical systems, IoT. $3 836359
700 1 $a Wang, Yan. $3 681237
700 1 $a Ji, Zhicheng. $3 917785
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-981-16-5959-1
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)