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Erschienen in: Neural Computing and Applications 12/2017

17.03.2016 | Original Article

Integration of industrial videogrammetry and artificial neural networks for monitoring and modeling the deformation or displacement of structures

verfasst von: Farshid Farnood Ahmadi

Erschienen in: Neural Computing and Applications | Ausgabe 12/2017

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Abstract

The need to monitor structures permanently and the necessity of performing measurements in a continuous space are of the most important factors which cause some restrictions, such as the rising cost, the dependence on the environment conditions and requirement for high-tech tools for permanent control of displacement and deformation of structures. Videogrammetry, which is used in different fields of industry and manufacturing as a precise and low-cost measurement method, can be utilized in this field. But the use of videogrammetry to control a structure deformation or displacement has four problems including synchronization of cameras in a permanent and long-term monitoring, the need for approximate values of unknown parameters, the necessity for automating the prediction of structure deformation or displacement and the need for high-speed computing. The evaluation of the system designed and implemented in this research shows that using videogrammetry based on the method presented in the research and the integration of videogrammetry and artificial neural networks can solve these problems. The system can be applied to produce the data which are needed for decision support systems to control displacement or deformation of structures intelligently.

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Metadaten
Titel
Integration of industrial videogrammetry and artificial neural networks for monitoring and modeling the deformation or displacement of structures
verfasst von
Farshid Farnood Ahmadi
Publikationsdatum
17.03.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 12/2017
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2255-2

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