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Research Projects
Project authority
Lehre
Forschung
Organisation
Virtual Data acquisition
01.01.2006 - 30.08.2009
Assigned research project
The aim of the project is the development of a software tool for an optimized and efficient design of wheel loaders and similar construction machines. The software tool will predict characteristic values of construction machines, which are not yet existent and differ from existing machinery in configuration oder dimension. These predictions will be made based on measurement data from existing machines, and characteristic values are e.g. overall load configurations for axle-torques. The effect of changes in design parameters like bucket width, wheel diameter, or traction force can therefore be predicted without building expensive prototypes. In order to efficiently acquire the necessary data from existing machines design of experiment techniques wil be uitilized. The prediction will be made using linear methods like regression analysis as well as nonlinear approaches like artifical neural networks.
People
Project leader
Martin Kozek
(E325)
Project personnel
Andrea Lorenz
(E325)
Institute
E325 - Institute of Mechanics and Mechatronics
Contract/collaboration
Liebherr-Werk Bischofshofen GmbH
Research focus
Sustainable and Low Emission Mobility: 10%
Computational System Design: 80%
Sustainable Production and Technologies: 10%
Keywords
German
English
Radlader
wheel loader
Virtuelle Messdatenerfassung
virtual data acquisition
Messdatenbank
measurement database
Publications
Publications