Fr. 333.00

Proceedings of the UNIfied Conference of DAMAS, IncoME and TEPEN Conferences (UNIfied 2025) - Volume 2

Englisch, Deutsch · Fester Einband

Erscheint am 21.11.2025

Beschreibung

Mehr lesen

This book gathers the latest advances, innovations, and applications in the field of condition monitoring, damage assessment, and maintenance engineering, as presented by leading international researchers and engineers at the UNIfied Conference of DAMAS (International Conference on Damage Assessment of Structures), International Conference on Maintenance Engineering (IncoME), and The Efficiency and Performance Engineering (TEPEN), held in Zhangjiajie, China, on May 16-19, 2025. Topics include machinery dynamics, sensors and measurement systems, signal processing, structural damage identification and machine fault diagnosis, plant maintenance and reliability, machine health monitoring, asset management, life-cycle cost optimization, 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.

Inhaltsverzeichnis

A machine learning based multi-dimensional equipment-level spare parts demand forecasting and support algorithm.- Contribution Title Temperature Compensation Extended Kalman Filter for Battery State of Charge Estimation via Recursive Least Squares Algorithm.- Confidential Computing Graph Similarity Protocol under the Malicious Model and its Applications in Blockchain.- Research on Fault Feature Extraction Method for Helicopter Main Reducer Based on CECP Approach.- Fault Detection in Offshore Wind Turbine Blades Based on Object Detection Techniques.- Normalized RMS for rotating machinery condition monitoring with the use of operation condition data.- Fault Feature Enhancement of Rolling Bearings Based on an Adaptive ENEMD.- Community Detection Method Based on Multi-view  Contrastive Mechanism.- A VMD-Transformer Framework for Voltage Degradation Prediction in Proton Exchange Membrane Fuel Cells.

Zusammenfassung

This book gathers the latest advances, innovations, and applications in the field of condition monitoring, damage assessment, and maintenance engineering, as presented by leading international researchers and engineers at the UNIfied Conference of DAMAS (International Conference on Damage Assessment of Structures), International Conference on Maintenance Engineering (IncoME), and The Efficiency and Performance Engineering (TEPEN), held in Zhangjiajie, China, on May 16-19, 2025. Topics include machinery dynamics, sensors and measurement systems, signal processing, structural damage identification and machine fault diagnosis, plant maintenance and reliability, machine health monitoring, asset management, life-cycle cost optimization, 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.

Produktdetails

Mitarbeit Bingyan Chen (Herausgeber), Bingyan Chen et al (Herausgeber), Xiong Shu (Herausgeber), Yun Zhu (Herausgeber), Hongxiang Zou (Herausgeber)
Verlag Springer, Berlin
 
Sprache Englisch, Deutsch
Produktform Fester Einband
Erscheint 21.11.2025
 
EAN 9783032013620
ISBN 978-3-0-3201362-0
Seiten 914
Illustration VI, 914 p. 499 illus., 441 illus. in color.
Serie Mechanisms and Machine Science
Themen Naturwissenschaften, Medizin, Informatik, Technik > Technik > Sonstiges

Maschinenbau, Elektronik, Robotik, Asset Management, manufacturing processes, Industrial and Production Engineering, reliability, Mechatronics, Machinery and Machine Elements, Robotic Engineering, Condition Monitoring, Maintenance Engineering, Damage Assessment, Machine Health Monitoring, Diagnostic Engineering

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