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Real-time Estimation of the Remaining Lifetime of Components

Real-time Estimation of the Remaining Lifetime of Components Simulation RE S E A R C H S I M U L AT I O N Real-time Estimation of the Remaining Lifetime of Components The availability of off-highway machines is gaining in importance, particularly with respect to seasonal use, such as agriculture. For example, machine failures can lead to considerable income losses during harvesting. At KIT, a method for the development of real-time capable models for the determination of the component loads of off-high - way machines was developed. The strength calculation of the piston of an axial piston pump serves as an example of use. The stresses in the component are determined by a multi-body simulation coupled with a structure simulation, and are then used to create an artificial neural network. The quality of the generated models is shown on the basis of the criteria accuracy, reproducibility and computation time. A U T HOR S Lars Brinkschulte, M. Sc. is Research Assistant at the Institute of Vehicle System Technology of the Karlsruhe Institute of Technology (KIT) in Karlsruhe (Germany). Prof. Dr.-Ing. Marcus Geimer is Director of the Institute of Vehicle System Technology of the Karlsruhe Institute of Technology (KIT) in Karlsruhe (Germany). © KIT 54 Simulation 1 M http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ATZoffhighway worldwide Springer Journals

Real-time Estimation of the Remaining Lifetime of Components

ATZoffhighway worldwide , Volume 10 (3) – Sep 8, 2017

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Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer Fachmedien Wiesbaden
Subject
Engineering; Automotive Engineering
eISSN
2366-1097
DOI
10.1007/s41321-017-0034-3
Publisher site
See Article on Publisher Site

Abstract

Simulation RE S E A R C H S I M U L AT I O N Real-time Estimation of the Remaining Lifetime of Components The availability of off-highway machines is gaining in importance, particularly with respect to seasonal use, such as agriculture. For example, machine failures can lead to considerable income losses during harvesting. At KIT, a method for the development of real-time capable models for the determination of the component loads of off-high - way machines was developed. The strength calculation of the piston of an axial piston pump serves as an example of use. The stresses in the component are determined by a multi-body simulation coupled with a structure simulation, and are then used to create an artificial neural network. The quality of the generated models is shown on the basis of the criteria accuracy, reproducibility and computation time. A U T HOR S Lars Brinkschulte, M. Sc. is Research Assistant at the Institute of Vehicle System Technology of the Karlsruhe Institute of Technology (KIT) in Karlsruhe (Germany). Prof. Dr.-Ing. Marcus Geimer is Director of the Institute of Vehicle System Technology of the Karlsruhe Institute of Technology (KIT) in Karlsruhe (Germany). © KIT 54 Simulation 1 M

Journal

ATZoffhighway worldwideSpringer Journals

Published: Sep 8, 2017

References