跳到主要导航 跳到搜索 跳到主要内容

A framework of particle missing compensation for particle tracking velocimetry via global optimization

  • Beihang University
  • State Key Laboratory of Aerodynamics
  • China Aerodynamics Research and Development Center

科研成果: 期刊稿件文章同行评审

摘要

Abstract: The performance of particle tracking velocimetry (PTV) is constrained by a practical issue, i.e., particle missing in a particle image frame. The randomly appeared loss-of-pair particles will bias the particle pairing relationship that is sought by particle matching algorithms. To handle this issue, this work proposes a general framework for the compensation of particle missing in PTV. Following our previous work (Nie in Exp Fluids 62(4): 68, 2021), we deal with the family of ant colony optimization (ACO) algorithms, which convert the task of particle matching to a global optimization problem for a particular objective function and seek a solution using ACO. To enable particle missing compensation, two core concepts are proposed. The first is to perform two symmetric ACOs from the forth and the back directions on a straddle-frame image pair, and then cross-validate the two sets of solutions to estimate the valid or problematic matching. The second is to make the action of the forth and the back ant colonies work in coordination with each other by sharing their knowledge on the particle matching relationship. This is implemented using an exterior loop, in which the intersection of the solutions obtained by the two colonies of ants, called mutual knowledge, will be learned and passed to the next generation. The first concept relies on an operation of virtual-particle add-on. It leads to the so-called cross-validation ant colony optimization (CVACO) algorithm. The second concept updates CVACO by dynamically adjusting the pheromone factor and the heuristic factor on each candidate particle pair in the next exterior pass, forming the so-called algorithms of pheromone-feedback CVACO (PF-CVACO) and heuristic-feedback CVACO (HF-CVACO), respectively. A synthetic test shows that the proposed algorithms work well in the scenarios of both single-frame particle missing and dual-frame particle missing at low-to-moderate particle missing rates, which cannot be well handled using conventional single-pass ACO. Graphical Abstract: [Figure not available: see fulltext.]

源语言英语
文章编号148
期刊Experiments in Fluids
63
9
DOI
出版状态已出版 - 9月 2022

指纹

探究 'A framework of particle missing compensation for particle tracking velocimetry via global optimization' 的科研主题。它们共同构成独一无二的指纹。

引用此