Tree internal defects detection method based on ResNet improved subspace optimization algorithm

IF 4.1 2区 材料科学 Q1 MATERIALS SCIENCE, CHARACTERIZATION & TESTING
Guoyang Liu , Hongwei Zhou , Hongju Zhou , Bo Xia , Yixuan Wu , Jie Shi
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引用次数: 0

Abstract

The erosion behavior of trunk borers leads to the destruction of trunk structure and the formation of internal defects, which significantly impacts the ecological and economic value of trees. Traditional non-destructive testing (NDT) methods are costly and have low resolution, whereas electromagnetic NDT methods are more suitable for high-resolution detection and imaging. However, solving the highly nonlinear electromagnetic inverse scattering problems (ISPs) for small-sized defects with high contrast is challenging. Therefore, this paper proposes an improved subspace optimization algorithm based on a ResNet network called SOM-ResNet. SOM-ResNet incorporates physical principles into deep learning networks by simulating the iterative process of induced current and contrast, thereby enhancing its ability to accurately detect small objects with high contrast. Experimental results demonstrate that SOM-ResNet outperforms single inversion algorithms in detecting complex scatterers with small to medium-sized targets, validating its excellent performance.

基于 ResNet 改进子空间优化算法的树内部缺陷检测方法
树干蛀虫的侵蚀行为会导致树干结构的破坏和内部缺陷的形成,从而严重影响树木的生态和经济价值。传统的无损检测(NDT)方法成本高、分辨率低,而电磁无损检测方法更适用于高分辨率检测和成像。然而,解决具有高对比度的小尺寸缺陷的高度非线性电磁反向散射问题(ISPs)具有挑战性。因此,本文提出了一种基于 ResNet 网络的改进型子空间优化算法,称为 SOM-ResNet。SOM-ResNet 通过模拟诱导电流和对比度的迭代过程,将物理原理融入深度学习网络,从而增强了其准确检测高对比度小物体的能力。实验结果表明,SOM-ResNet 在检测中小型目标的复杂散射体方面优于单一反演算法,验证了其卓越的性能。
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来源期刊
Ndt & E International
Ndt & E International 工程技术-材料科学:表征与测试
CiteScore
7.20
自引率
9.50%
发文量
121
审稿时长
55 days
期刊介绍: NDT&E international publishes peer-reviewed results of original research and development in all categories of the fields of nondestructive testing and evaluation including ultrasonics, electromagnetics, radiography, optical and thermal methods. In addition to traditional NDE topics, the emerging technology area of inspection of civil structures and materials is also emphasized. The journal publishes original papers on research and development of new inspection techniques and methods, as well as on novel and innovative applications of established methods. Papers on NDE sensors and their applications both for inspection and process control, as well as papers describing novel NDE systems for structural health monitoring and their performance in industrial settings are also considered. Other regular features include international news, new equipment and a calendar of forthcoming worldwide meetings. This journal is listed in Current Contents.
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