含缺陷固体火箭发动机燃面自适应提取算法

固体火箭发动机CT图像存在的伪影噪声会严重影响初始燃面边界与缺陷的提取,并且实际CT图像中缺陷信息提取困难,研究有效地去掉CT图像中伪影并自动提取出燃面数据与缺陷数据的算法具有重要的工程实际价值。针对CT图像去伪影与缺陷提取难的问题,提出一种IBM3D滤波算法,在块匹配阶段利用边缘检测的先验信息寻找相似块;并提出一种自适应Canny边缘检测算法与种子八连通标记法相结合的方式将图像中的初始燃面与缺陷数据有序地分离出来。实验结果表明IBM3D算法的峰值信噪比与结构相似性水平较其他算法更高,自适应边缘检测算法提取的燃面缺陷信息较其他算法更为完整。实现了含缺陷的固体火箭发动机CT图像质量的提升,并准确地提取初始燃面、缺陷信息。

Adaptive extraction algorithm of burning surface of solid rocket motor with defects

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.