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Force Identification Based on Response Signals Captured with High-Speed Three-Dimensional Digital Image Correlation.

Krzysztof MendrokÁngel Jesús Molina-ViedmaElias López-AlbaFrancisco A Díaz GarridoŁukasz Pieczonka
Published in: Sensors (Basel, Switzerland) (2023)
Structural Health Monitoring (SHM) systems allow three types of diagnostic tasks to be performed, namely damage identification, loads monitoring, and damage prognosis. Only if all three tasks are correctly fulfilled can the useful remaining life of a structure be estimated credibly. This paper deals with the second task and aimed to extend state-of-the-art in load identification, by demonstrating that it is feasible to achieve it through the analysis of response signals captured with high-speed three-dimensional Digital Image Correlation (HS 3D-DIC). The efficacy of the proposed procedure is demonstrated experimentally on a frame structure under broadband vibration excitation. Full-field vibration displacement signals are captured with the use of two high-speed cameras and processed with 3D-DIC. Loads are identified with two different algorithms based on inverting the Frequency Response Function (FRF) matrix and modal filtration (MF). The paper discusses both methods providing their theoretical background and experimental performance.
Keyphrases
  • high speed
  • atomic force microscopy
  • high resolution
  • deep learning
  • oxidative stress
  • healthcare
  • public health
  • working memory
  • machine learning
  • high frequency
  • bioinformatics analysis
  • risk assessment