Advances in Asset Management and Condition Monitoring : COMADEM 2019 / edited by Andrew Ball, Len Gelman, B. K. N. Rao

Mitwirkende(r):

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Smart Innovation, Systems and Technologies ; 166 | Springer eBook CollectionVerlag: Cham : Springer International Publishing, 2020Verlag: Cham : Imprint: Springer, 2020Auflage: 1st ed. 2020Beschreibung: 1 Online-Ressource(XXII, 1566 p. 903 illus., 744 illus. in color.)ISBN:

9783030577452

Schlagwörter:

620 23

DOI: DOI: 10.1007/978-3-030-57745-2Online-Ressourcen:

Zusammenfassung: Asset Management -- Condition Monitoring -- Structural Health Monitoring -- A Meshing Resonance based Demodulation Algorithm and its Application for Planet Gear Tooth Root Crack Detection -- Exploring the Impacts of Using Mobile Collaborative Augmented Reality on the Field Service Business Model of Capital Goods Manufacturing Companies -- Research and Implementation of Real-time Motion Control of Robot based on Kinect.Zusammenfassung: This book gathers select contributions from the 32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2019), held at the University of Huddersfield, UK in September 2019, and jointly organized by the University of Huddersfield and COMADEM International. The aim of the Congress was to promote awareness of the rapidly emerging interdisciplinary areas of condition monitoring and diagnostic engineering management. The contents discuss the latest tools and techniques in the multidisciplinary field of performance monitoring, root cause failure modes analysis, failure diagnosis, prognosis, and proactive management of industrial systems. There is a special focus on digitally enabled asset management and covers several topics such as condition monitoring, maintenance, structural health monitoring, non-destructive testing and other allied areas. Bringing together expert contributions from academia and industry, this book will be a valuable resource for those interested in latest condition monitoring and asset management techniques. .PPN: PPN: 1728470838Package identifier: Produktsigel: ZDB-2-ENG | ZDB-2-SEB | ZDB-2-SXE

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