Proceedings of IncoME-VI and TEPEN 2021 : Performance Engineering and Maintenance Engineering / edited by Hao Zhang, Guojin Feng, Hongjun Wang, Fengshou Gu, Jyoti K. Sinha

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Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Mechanisms and Machine Science ; 117Verlag: Cham : Springer International Publishing, 2023Verlag: Cham : Imprint: Springer, 2023Auflage: 1st ed. 2023Beschreibung: 1 Online-Ressource(XIV, 1102 p. 709 illus., 571 illus. in color.)ISBN:

9783030990756

Schlagwörter:

Andere physische Formen: 9783030990749 | 9783030990763 | 9783030990770 | Erscheint auch als: 9783030990749 Druck-Ausgabe | Erscheint auch als: 9783030990763 Druck-Ausgabe | Erscheint auch als: 9783030990770 Druck-AusgabeDOI: DOI: 10.1007/978-3-030-99075-6Online-Ressourcen:

Zusammenfassung: Chapter 1: An Optical Gyroscope Based Technique for Calibrating Angular-Measuring Instrument -- Chapter 2: Data Analysis for Predictive Maintenance Using Time Series and Deep Learning Models – A Case Study in a Pulp Paper Industry -- Chapter 3: Reinforcement Learning Fault Diagnosis Method Based on Less Tag Data -- Chapter 4: Optimization design and simulation analysis of miniature boring machine based on ADAMS. .Zusammenfassung: This volume gathers the latest advances, innovations and applications in the field of condition monitoring, plant maintenance and reliability, as presented by leading international researchers and engineers at the 6th International Conference on Maintenance Engineering and the 2021 conference of the Efficiency and Performance Engineering Network (IncoME-VI TEPEN 2021), held in Tianjin, China on October 20-23, 2021. Topics include vibro-acoustics monitoring, condition-based maintenance, sensing and instrumentation, machine health monitoring, maintenance auditing and organization, non-destructive testing, reliability, asset management, condition monitoring, life-cycle cost optimisation, prognostics and health management, maintenance performance measurement, manufacturing process monitoring, and robot-based monitoring and diagnostics. The contributions, which were selected through a rigorous international peer-review process, share exciting ideas that will spur novel research directions and foster new multidisciplinary collaborations.PPN: PPN: 1816991449Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-ENG | ZDB-2-SXE

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