Autonomous spatially-adaptive sampling in experiments based on curvature, statistical error and sample spacing with applications in LDA measurements

Raf Theunissen, Jesse S Kadosh, Christian B Allen

Research output: Contribution to journalArticle (Academic Journal)peer-review

6 Citations (Scopus)
308 Downloads (Pure)

Abstract

Spatially varying signals are typically sampled by collecting uniformly spaced samples irrespective of the signal content. For signals with inhomogeneous information content, this leads to unnecessarily dense sampling in regions of low interest or insufficient sample density at important features, or both. A new adaptive sampling technique is presented directing sample collection in proportion to local information content, capturing adequately the short-period features while sparsely sampling less dynamic regions. The proposed method incorporates a data-adapted sampling strategy on the basis of signal curvature, sample space-filling, variable experimental uncertainty and iterative improvement. Numerical assessment has indicated a reduction in number of samples required to achieve a predefined uncertainty level overall while improving local accuracy for important features. The potential of the proposed method has been further demonstrated on the basis of Laser Doppler Anemometry experiments examining the wake behind a NACA0012 airfol and the boundary layer characterisation of a flat plate.
Original languageEnglish
Article number116
Number of pages18
JournalExperiments in Fluids
Volume56
Early online date27 May 2015
DOIs
Publication statusPublished - Jun 2015

Keywords

  • Adaptive sampling
  • curvature
  • uncertainty
  • radial basis function
  • LDA
  • boundary layer
  • airfoil

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