Adaptive extraction algorithm of burning surface of solid rocket motor with defects
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School of Aircraft Engineering, Nanchang Hangkong University,Nanchang 330063, China

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V435

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    Abstract:

    The artifact noise present in the CT image of a solid rocket engine will seriously affect the extraction of the initial combustion surface boundary and defects, and the extraction of defect information in the actual CT image is difficult.The algorithm that effectively removes CT image artifacts and automatically extracts the burn surface and defect data has important engineering practical value. Aiming at the problems of CT image de-artifacting and defect extraction, an IBM3D filtering algorithm is proposed, which uses the a priori information of edge detection to find similar blocks in the block matching stage. In addition, an adaptive Canny edge detection algorithm combined with seed eight connected labeling method is proposed to orderly separate the initial burning surface and defect data in the image. The experimental results show that the peak signal-to-noise ratio and structural similarity of the IBM3D algorithm are higher than other algorithms, and the fire surface defect information extracted by the adaptive edge detection algorithm is more complete than other algorithms.The CT image quality of solid rocket motor with defects is improved, and the initial burning surface and defect information are extracted accurately.

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  • Received:
  • Revised:
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  • Online: February 22,2024
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