Volume 49 Issue 11
Nov.  2023
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LIU S,LU H Y,ZHANG W W,et al. Fast algorithm for grain burnback of actually shaped grains of solid motor[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(11):3115-3123 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0795
Citation: LIU S,LU H Y,ZHANG W W,et al. Fast algorithm for grain burnback of actually shaped grains of solid motor[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(11):3115-3123 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0795

Fast algorithm for grain burnback of actually shaped grains of solid motor

doi: 10.13700/j.bh.1001-5965.2021.0795
Funds:  Natural Science Foundation of Jiangxi Province (20201BBE51002); Jiangxi Province Graduate Student Innovation Special Fund Project (YC2021-S685)
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  • Corresponding author: E-mail:13964508115@163.com
  • Received Date: 31 Dec 2021
  • Accepted Date: 23 Apr 2022
  • Publish Date: 10 May 2022
  • A fast minimum distance function method for CT data (CT-FMDF) is proposed to address the artifact noise in CT image data of solid rocket motors, the large combustion surface roughness of actually formed grains, and the difficulty in transition calculation. The non-local means (NLM) filtering algorithm is used to denoise the CT images. Then, the Canny edge detection improved by the Scharr operator is used to extract the initial burning surface of the grains from the de-artifacted image. The maximum between-class variance algorithm (OTSU) separates the grains, establishing a three-dimensional volume data model of grains, and multiple parallel K-dimension trees for the combustion surface data. The minimum distance from the grains to the combustion surface is quickly retrieved. The experimental results show that for different grains structures, the position of a burning surface at any thickness can be achieved and that the algorithm has a shorter running time. For the grains with initial burning surface defects, the effect of the defects on the burning surface during combustion can be calculated based on the actual CT data.

     

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