Digital Image Correlation based ANN networks for evaluating the prestressing forces in civil Engineering structures
Abstract
The methods currently used in engineering practice for testing and checking the magnitude of the pretensioning force actually present in mechanical fasteners can only be recorded inadequately without contact. There are visual assessment methods as well as electronic measuring methods which, however, only partially provide satisfactory results - in terms of accuracy as well as instrumentation. In this research project newly developed innovative methods of Digital Image Correlation methods for testing and controlling the preload forces in mechanical fasteners are tested for their feasibility and applicability. Experiments with Digital Image Correlation methods on similar components as bolted joints have already shown very good results and are therefore promising for the application on bolted joints. In order to investigate the quality of information and long-term stability of the newly developed method using DIC, for testing and controlling the pretensioning forces in mechanical fasteners, DIC tests are to be carried out in this project and the results obtained are to be evaluated according to their applicability in series Translated with www.DeepL.com/Translator (free version)
Schlagworte Neuronale Net Prediction Models Reliability Assessment
Publikationen
Mitarbeiter*innen
Alfred Strauss
Univ.Prof. Dipl.-Ing. Dr. Alfred Strauss
alfred.strauss@boku.ac.at
Tel: +43 1 47654-87511
Project Leader
01.06.2020 - 31.10.2020