首页> 外文会议>International Conference on Logistics Systems and Intelligent Management >Two Dimensional Image Reconstruction of Log Cross-section Defect Based on Stress Wave Technique
【24h】

Two Dimensional Image Reconstruction of Log Cross-section Defect Based on Stress Wave Technique

机译:基于应力波技术的日志横截面缺陷二维图像重建

获取原文
获取外文期刊封面目录资料

摘要

Wood is a material that is produced biologically in the growing tree, making it vulnerable to the attack of fungi. This will reduce the quality of wood, especially for log. The 2D image reconstruction contributed greatly for log cross-section defect testing in order to promote the utilization rate of wood resources. At first, this paper studied the stress wave computerized tomography technique, and introduced the straight-line tracing technique and the Algebraic Reconstruction Technique (ART) algorithm. Then, the medium model was constructed for numerical simulation analysis. The reconstruction of the medium model was conducted using straight line tracing - ART algorithm, and the impact of the number of iterations for image reconstruction accuracy was analyzed. At last, this paper validated the feasibility for two-dimensional image reconstruction of log internal defects using this method by physical model testing. Empirical and medium model results showed that the convergence of straight line tracing - ART algorithm was fast and reconstruction image was good. The two-dimensional image reconstruction of log internal defects could basically be realized using the straight line tracing-algebraic reconstruction algorithm method. And the feasibility and practicality of theory and technique that proposed in this paper were validated by practical testing.
机译:木材是一种在生长树上生物生产的材料,使其容易受到真菌的攻击。这将降低木材的质量,特别是对于日志。 2D图像重建为日志横截面缺陷测试提供了大大贡献,以促进木材资源的利用率。首先,本文研究了应力波电脑断层扫描技术,并引入了直线跟踪技术和代数重建技术(ART)算法。然后,构建介质模型以用于数值模拟分析。通过直线跟踪 - 技术算法进行介质模型的重建,分析了图像重建精度的迭代次数的影响。最后,本文通过物理模型测试验证了使用此方法使用此方法对日志内部缺陷的二维图像重建的可行性。实证和中型模型结果表明,直线跟踪算法的趋同快速,重建图像良好。可以使用直线跟踪代理重建算法方法基本上实现了日志内部缺陷的二维图像重建。并通过实际测试验证了本文提出的理论和技术的可行性和实用性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号