Detail publikace

Loading condition monitoring on trusses applying a machine learning approach with training data of a finite element model: A study case

Tinoco, H. A., & Cardona, C. I.

Originální název

Loading condition monitoring on trusses applying a machine learning approach with training data of a finite element model: A study case

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Structural health monitoring (SHM) techniques deal with the changes in the dynamic or static characteristics of the structures that affect its performance during the service [1]. Mainly, these techniques are based on vibrations, and their implementation includes complex integrated systems not addressed from the structural design. Despite the numerous applications of SHM, loading condition monitoring (application place, direction, and magnitude) is not a very implemented strategy in this engineering field. This paper presents a methodology to monitor the application of external forces on structures using a learning machine process and finite element analysis (FEA). In Figure 1a is described the proposed monitoring methodology, which is applied to a truss structure to validate this study. The truss contains nine structural elements, and each one presents a piezoelectric transducer to measure the forces in their links, as illustrated in Figure 1b. The real truss was modeled by means of a FEA (implemented in Matlab with truss elements) considering their mechanical properties and loading conditions, as observed in Figure 1c. To simulate different loading conditions, a force F_s is applied in node 3 varying two parameters, angle β, and magnitude. This is carried out to establish a database using the internal forces (in each bar) obtained by FEA.

Klíčová slova

Machine learning, loading monitoring, Finite element method

Autoři

Tinoco, H. A., & Cardona, C. I.

Vydáno

4. 11. 2019

Nakladatel

University of West Bohemia,

Místo

Plzen, Czech Republic

ISBN

978-80-261-0889-4

Kniha

Proceedings of 35th conference Computational Mechanics 2019

Edice

Vítezslav Adámek

Číslo edice

35

Strany od

205

Strany do

206

Strany počet

3

BibTex

@inproceedings{BUT167362,
  author="Hector Andres {Tinoco Navarro}",
  title="Loading condition monitoring on trusses applying a machine learning approach with training data of a finite element model: A study case",
  booktitle="Proceedings of 35th conference Computational Mechanics 2019",
  year="2019",
  series="Vítezslav Adámek",
  number="35",
  pages="205--206",
  publisher="University of West Bohemia,",
  address="Plzen, Czech Republic",
  isbn="978-80-261-0889-4"
}