Ndt & E International最新文献_第9页

Evaluation of microcrack caused by freeze–thawing in wet mortar using ultrasonic velocities of multiple frequencies 用多频超声速度评价湿砂浆冻融微裂纹

IF 4.5 2区材料科学 Q1 MATERIALS SCIENCE, CHARACTERIZATION & TESTING

Ndt & E International

Pub Date : 2026-03-01 Epub Date: 2025-10-19 DOI: 10.1016/j.ndteint.2025.103583

Takuya Horikawa , Ryosuke Umezawa , Satoru Nakashima , Makoto Katsura

This paper proposes a method for determining the characteristics of microcracks in wet mortars caused by frost damage, from ultrasonic velocities measured at multiple frequencies. In partially water-saturated mortar, P-wave propagation induces pressure gradients between the saturated and dried regions. This is followed by pore water flow, called mesoscopic-scale wave-induced fluid flow (WIFF). It results in the viscoelastic behavior of the dynamic moduli, and their frequency dependency reflects the mobility of pore water related to the crack properties. The integration of the cracked effective medium (CEM) theory and mesoscopic-scale WIFF model enables the description of the frequency-dependent moduli of cracked mortars as functions of crack porosity, width, and water saturation. Numerical simulations were conducted initially to evaluate the effects of crack properties and saturation on the moduli. The simulations demonstrated that the crack aperture significantly influenced the reduction in mortar frame moduli and that the frequency dependency of the P-wave velocity was sensitive to the water saturation, as well as the crack properties. Subsequently, P- and S-wave velocity measurements were performed on mortar specimens subjected to freeze–thaw cycles (FTCs). The crack porosity, width, and water saturation were evaluated simultaneously using the proposed method. The obtained crack porosity was consistent with the porosity variation before and after FTCs. The obtained crack width agreed with the variation in pore size distribution. The CEM-WIFF method can be used to evaluate the generation and progress of microcracks in mortar constructions by continuously or periodically measuring the ultrasonic velocities at multiple frequencies.

本文提出了一种利用多频率超声测速来测定湿砂浆冻损微裂纹特征的方法。在部分水饱和砂浆中，纵波传播在饱和区和干燥区之间引起压力梯度。其次是孔隙水流动，称为介观尺度波致流体流动（WIFF）。动态模量具有粘弹性特性，其频率依赖性反映了孔隙水的流动性与裂缝性质的关系。裂缝有效介质（CEM）理论与细观尺度WIFF模型的结合，可以描述裂缝砂浆的频率相关模量作为裂缝孔隙度、宽度和含水饱和度的函数。初步进行了数值模拟，以评估裂纹特性和饱和度对模量的影响。模拟结果表明，裂缝孔径对砂浆框架模量的降低有显著影响，纵波速度的频率依赖关系对含水饱和度和裂缝特性都很敏感。随后，对冻融循环（FTCs）下的砂浆试件进行了纵波和横波速度测量。同时对裂缝孔隙度、宽度和含水饱和度进行了评价。得到的裂纹孔隙率与FTCs前后孔隙率的变化一致。得到的裂缝宽度与孔隙尺寸分布的变化一致。CEM-WIFF方法可以通过连续或周期性地测量多频率的超声速度来评估砂浆结构微裂纹的产生和发展。

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引用次数: 0

Detection of debonding in stiffened composite panels by acoustic nonlinear response of broadband ultrasonic guided waves 宽带超声导波非线性声响应检测加筋复合材料板的脱粘

IF 4.5 2区材料科学 Q1 MATERIALS SCIENCE, CHARACTERIZATION & TESTING

Ndt & E International

Pub Date : 2026-03-01 Epub Date: 2025-09-23 DOI: 10.1016/j.ndteint.2025.103561

Yi Luo , Zifeng Lan , Yajie Hu , Changyu Zhang , Mingxi Deng , Weibin Li

Debonding defects in the bonding layers of stiffened composite panels pose significant safety risks. However, they are challenging to detect due to their deep location and complex geometry, where conventional linear ultrasonic methods often fail. This study presents a broadband nonlinear ultrasonic guided wave approach for accurate debonding imaging. Chirp guided wave mixing (CGWM) is employed to excite broadband signals and effectively eliminate time-consuming signal processing. Defects are detected by analyzing three types of nonlinear components: second-harmonic generation (SHG), sum-frequency harmonic (SFH), and difference-frequency harmonic (DFH) responses. Results demonstrate that while linear ultrasonic detection struggles with deep debonding, all nonlinear ultrasonic components enable successful defect identification and imaging. Crucially, SFH and DFH allow efficient frequency-domain filtering, significantly reducing computational time compared to time-frequency domain processing required for SHG. Furthermore, the CGWM technique enhances nonlinear source behavior at defects while minimizing spurious nonlinearities from instruments.

加筋复合板粘接层的脱粘缺陷存在较大的安全隐患。然而，由于其深层位置和复杂的几何形状，它们的检测具有挑战性，而传统的线性超声方法往往失败。本研究提出一种宽频带非线性超声导波方法用于精确的脱粘成像。利用啁啾导波混频（CGWM）对宽带信号进行激励，有效地消除了耗时的信号处理。通过分析三种非线性分量：二次谐波（SHG）、和频谐波（SFH）和差频谐波（DFH）响应来检测缺陷。结果表明，当线性超声检测与深度脱粘斗争时，所有非线性超声分量都能够成功地识别和成像缺陷。重要的是，SFH和DFH允许有效的频域滤波，与SHG所需的时频域处理相比，显著减少了计算时间。此外，CGWM技术增强了缺陷处的非线性源行为，同时最大限度地减少了仪器产生的伪非线性。

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引用次数: 0

Physics-aware state space network with uncertainty quantification for automated defect detection in infrared NDT thermography 红外无损检测热成像仪缺陷自动检测的不确定量化物理感知状态空间网络

IF 4.5 2区材料科学 Q1 MATERIALS SCIENCE, CHARACTERIZATION & TESTING

Ndt & E International

Pub Date : 2026-03-01 Epub Date: 2025-10-27 DOI: 10.1016/j.ndteint.2025.103586

Mohammed Umar Jibril , Bin Gao , Wai Lok Woo , Guanquan Tian , Nabeel Ahmed Khan , Rabiu Sale Zakariyya , Amina Jibril Muhammad

We present PASS-Net, a physics-guided deep learning framework for automated defect segmentation in infrared non-destructive testing (NDT) of composite materials. The architecture uniquely integrates a U-Net backbone with Fourier-based physics-aware layers and bidirectional State-Space Models (SSMs) to capture both spatial patterns and temporal thermal dynamics. By incorporating thermal diffusion principles directly into the network architecture, the model ensures thermodynamically consistent predictions while maintaining computational efficiency. The SSM enables effective long-range dependency modeling with linear complexity, addressing limitations of traditional attention mechanisms. Moreover, the framework delivers a comprehensive uncertainty analysis by combining inference-time stochastic dropout with evaluation on multiple augmented input variants, decomposing total uncertainty into epistemic and aleatoric components for reliable decision-making in safety-critical contexts. Validated on aerospace-grade composites, such as CFRP and fiberglass, PASS-Net outperforms traditional U-Net models, achieving at least 6% improvement in mean Intersection over Union (mIoU). It demonstrates resilience to real-world challenges, including material heterogeneity and non-uniform heating, making it suitable for industrial-scale deployment. A comparative analysis further reveals a superior defect contrast-to-noise ratio, highlighting the model’s potential for adoption in industrial non-destructive testing (NDT) applications that require both accuracy and computational efficiency. The integrated physics-based loss ensures consistent performance across diverse materials and operational conditions, representing a significant step toward reliable, deployable deep learning solutions in non-destructive testing (NDT). The implementation, including code and datasets, is available in https://faculty.uestc.edu.cn/gaobin/zh_CN/lwcg/153392/list/index.htm.

我们提出了PASS-Net，一个物理指导的深度学习框架，用于复合材料红外无损检测（NDT）中的自动缺陷分割。该体系结构独特地将U-Net骨干网与基于傅里叶的物理感知层和双向状态空间模型（ssm）集成在一起，以捕获空间模式和时间热动力学。通过将热扩散原理直接纳入网络架构，该模型在保持计算效率的同时确保了热力学一致的预测。SSM支持有效的具有线性复杂性的远程依赖建模，解决了传统注意力机制的局限性。此外，该框架通过将推理时间随机退出与对多个增强输入变量的评估相结合，提供了全面的不确定性分析，将总不确定性分解为认知和任意成分，以便在安全关键环境中进行可靠的决策。在航空级复合材料（如CFRP和玻璃纤维）上进行验证后，PASS-Net优于传统的U-Net模型，平均交联（mIoU）提高了至少6%。它展示了对现实世界挑战的弹性，包括材料的异质性和不均匀加热，使其适合工业规模的部署。对比分析进一步揭示了优越的缺陷对比度-噪声比，突出了该模型在需要准确性和计算效率的工业无损检测（NDT）应用中的应用潜力。基于物理的集成损耗确保了在不同材料和操作条件下的一致性能，代表了在无损检测（NDT）中可靠、可部署的深度学习解决方案的重要一步。实现，包括代码和数据集，可在https://faculty.uestc.edu.cn/gaobin/zh_CN/lwcg/153392/list/index.htm中获得。

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引用次数: 0

Enhanced crack profile identification using physics-informed thresholding from digital image correlation techniques 利用数字图像相关技术的物理信息阈值增强裂纹轮廓识别

IF 4.5 2区材料科学 Q1 MATERIALS SCIENCE, CHARACTERIZATION & TESTING

Ndt & E International

Pub Date : 2026-03-01 Epub Date: 2025-10-17 DOI: 10.1016/j.ndteint.2025.103584

Cheng Chen , Liuyang Feng

This paper proposes a novel method to identify the fatigue crack profile using physics-informed indicator derived from digital image correlation (DIC). The physics-informed indicator allows segmentation of crack profiles by applying thresholding to the displacement gradient field. The optimized threshold criteria derive from a GPR-based training process and finite element models. The experimental tests of the modified single edge notched tension specimens validate the crack sizing accuracy of the proposed approach under mixed-mode conditions. This study compares the crack trajectory tracking accuracy among different approaches: the proposed DIC approach, the edge detection method and manual measurement under various image and crack conditions. The physics-informed DIC approach demonstrates enhanced accuracy and robustness than the conventional image tools, especially under compromised image qualities and human-eye-invisible crack conditions.

提出了一种基于数字图像相关（DIC）的物理信息指示器识别疲劳裂纹轮廓的新方法。该物理指标可以通过对位移梯度场应用阈值来分割裂缝剖面。优化的阈值标准来源于基于gpr的训练过程和有限元模型。对改进后的单棱缺口拉伸试件进行了试验，验证了该方法在混合模态条件下的裂纹定值精度。在不同的图像和裂纹条件下，比较了本文提出的DIC方法、边缘检测方法和人工测量方法对裂纹轨迹的跟踪精度。基于物理的DIC方法比传统的图像工具具有更高的准确性和鲁棒性，特别是在图像质量受损和人眼不可见的裂缝条件下。

引用次数: 0

Noise reduction for LDC resonant eddy current using multi-scale dual-parameter reinforced-learning fusion 基于多尺度双参数强化学习融合的LDC谐振涡流降噪方法

IF 4.5 2区材料科学 Q1 MATERIALS SCIENCE, CHARACTERIZATION & TESTING

Ndt & E International

Pub Date : 2026-03-01 Epub Date: 2025-09-19 DOI: 10.1016/j.ndteint.2025.103546

Xiaolong Lu , Feilong Peng , Zongwen Wang , Maolin Luo , Qiuji Yi , Guiyun Tian

This paper presents a novel methodology for mitigating vibration-induced distortions in rail surface defect detection through eddy current testing. We developed a dual-parameter eddy current sensor utilizing the LDC1101 (inductive digital converter). The sensor exploits the fundamental relationship between parallel impedance (R_P) and inductance (L) to establish a dual-parameter fusion model that effectively reduces vibration interference during detection. Sensor sensitivity is enhanced through Litz Wire implementation. Our numerical simulations compare the defect detection capabilities of Litz Wire versus single-core coils, while examining the Litz Wire’s response characteristics during dual-parameter detection. These analyses also elucidate the mechanisms underlying anomalous R_P responses. Laboratory and field trials validate the methodology’s efficacy in suppressing vibration interference during eddy current detection, demonstrating the probe’s reliability for surface defect detection in rail production.

本文提出了一种通过涡流检测来减轻钢轨表面缺陷检测中振动引起的畸变的新方法。我们利用电感式数字转换器LDC1101开发了一种双参数涡流传感器。该传感器利用并联阻抗（RP）和电感(L)之间的基本关系，建立了双参数融合模型，有效降低了检测过程中的振动干扰。通过Litz Wire实现增强了传感器灵敏度。我们的数值模拟比较了Litz Wire与单芯线圈的缺陷检测能力，同时研究了Litz Wire在双参数检测时的响应特性。这些分析还阐明了异常RP反应的机制。实验室和现场试验验证了该方法在涡流检测过程中抑制振动干扰的有效性，证明了探头在钢轨生产中表面缺陷检测的可靠性。

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引用次数: 0

Multi-directional shearography for high-precision localization of near-surface defects 面向近表面缺陷高精度定位的多方向剪切成像

IF 4.5 2区材料科学 Q1 MATERIALS SCIENCE, CHARACTERIZATION & TESTING

Ndt & E International

Pub Date : 2026-03-01 Epub Date: 2025-09-11 DOI: 10.1016/j.ndteint.2025.103536

Guanlin Li , Yao Hu , Qun Hao

Shearography is an effective technique for detecting and localizing near-surface defects in engineering materials. However, as critical experimental parameters in shearography, both the loading magnitude and shearing magnitude can lead to localization errors or even misjudgment. Although existing shearography-based approaches have made progress in defect localization, challenges remain in achieving both high localization accuracy and robustness. To address these challenges, we propose a novel framework combining two key innovations: (1) a multi-directional shearography system to separate and eliminate errors caused by shearing magnitude, and (2) a criterion for optimal loading magnitude selection to suppress errors caused by loading magnitude. Using our method, we performed defect localization on a test object containing three types of defects. Experimental results demonstrate that, within a suitable range of loading magnitude, our method achieves a relative error of 3.6 % in the defect area (indicating size accuracy) and an average intersection over union of 0.8156 (reflecting overlap consistency with ground truth). Furthermore, key parameters of multi-directional shearography are analysis, and defects with extreme aspect ratios are localized, demonstrating the superior performance of our method.

剪切成像技术是工程材料近表面缺陷检测和定位的有效技术。然而，作为剪切学的关键实验参数，加载幅度和剪切幅度都可能导致定位误差甚至误判。尽管现有的基于剪切图的方法在缺陷定位方面取得了进展，但在实现高定位精度和鲁棒性方面仍然存在挑战。为了应对这些挑战，我们提出了一个结合两个关键创新的新框架：(1)一个多向剪切成像系统，以分离和消除剪切幅度引起的误差；(2)一个最佳加载幅度选择准则，以抑制加载幅度引起的误差。使用我们的方法，我们在包含三种类型缺陷的测试对象上执行缺陷定位。实验结果表明，在合适的加载幅度范围内，我们的方法在缺陷区域的相对误差为3.6%（表明尺寸精度），平均相交比并为0.8156（反映了与地面真实的重叠一致性）。对多向剪切成像的关键参数进行了分析，对高宽比极值缺陷进行了定位，验证了该方法的优越性。

{"title":"Multi-directional shearography for high-precision localization of near-surface defects","authors":"Guanlin Li , Yao Hu , Qun Hao","doi":"10.1016/j.ndteint.2025.103536","DOIUrl":"10.1016/j.ndteint.2025.103536","url":null,"abstract":"<div><div>Shearography is an effective technique for detecting and localizing near-surface defects in engineering materials. However, as critical experimental parameters in shearography, both the loading magnitude and shearing magnitude can lead to localization errors or even misjudgment. Although existing shearography-based approaches have made progress in defect localization, challenges remain in achieving both high localization accuracy and robustness. To address these challenges, we propose a novel framework combining two key innovations: (1) a multi-directional shearography system to separate and eliminate errors caused by shearing magnitude, and (2) a criterion for optimal loading magnitude selection to suppress errors caused by loading magnitude. Using our method, we performed defect localization on a test object containing three types of defects. Experimental results demonstrate that, within a suitable range of loading magnitude, our method achieves a relative error of 3.6 % in the defect area (indicating size accuracy) and an average intersection over union of 0.8156 (reflecting overlap consistency with ground truth). Furthermore, key parameters of multi-directional shearography are analysis, and defects with extreme aspect ratios are localized, demonstrating the superior performance of our method.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"158 ","pages":"Article 103536"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced detection of impact damage in CFRP based on a novel eddy current probe 基于新型涡流探头的CFRP冲击损伤增强检测

IF 4.5 2区材料科学 Q1 MATERIALS SCIENCE, CHARACTERIZATION & TESTING

Ndt & E International

Pub Date : 2026-03-01 Epub Date: 2025-10-07 DOI: 10.1016/j.ndteint.2025.103573

Rongyan Wen, Chongcong Tao, Hongli Ji, Yuqing Qiu, Jinhao Qiu

Carbon Fiber Reinforced Plastic (CFRP) composites are susceptible to damage and defects, which may arise during manufacturing or operational stages, potentially compromising structural integrity. This study introduces a novel eddy current detection probe featuring a nine-grid design, which enhances spatial resolution and sensitivity for detecting impact damage in CFRP. The excitation coils of the probe were optimized to concentrate the majority of the eddy current energy in the localized CFRP region directly beneath the probe, thereby significantly enhancing detection sensitivity and performance. Utilizing excitation coils with phase variations, the probe generates an elliptically polarized electric field with rotational characteristics, facilitating more effective detection of impact-induced defects than conventional probes with linearly polarized fields. Validation experiments were carried out where the nine-grid probe showed a significant enhancement in detecting CFRP impact damage. The damage area can be quantified from the eddy current signal with a thresholding method which shows a positive correlation with the impact energy

< 6 J

in CFRP orthotropic plates.

碳纤维增强塑料（CFRP）复合材料容易受到损坏和缺陷，这可能在制造或操作阶段出现，潜在地损害结构完整性。本文介绍了一种新型的涡流检测探头，该探头采用九网格设计，提高了CFRP冲击损伤检测的空间分辨率和灵敏度。优化了探头的激励线圈，将大部分涡流能量集中在探头正下方的CFRP局部区域，从而显著提高了探测灵敏度和性能。利用相位变化的激励线圈，探头产生具有旋转特性的椭圆极化电场，比传统的线极化探头更有效地检测冲击缺陷。在验证实验中，九网格探针在检测CFRP冲击损伤方面表现出显著的增强。采用阈值法可从涡流信号量化CFRP正交各向异性板的损伤面积，损伤面积与冲击能<；6J呈正相关。

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引用次数: 0

Automated image stitching of ultrasonic C-scan thickness data 超声c扫描厚度数据的自动图像拼接

IF 4.5 2区材料科学 Q1 MATERIALS SCIENCE, CHARACTERIZATION & TESTING

Ndt & E International

Pub Date : 2026-03-01 Epub Date: 2025-10-21 DOI: 10.1016/j.ndteint.2025.103581

Alexandru Nichita, Yifeng Zhang, Frederic Cegla

This study investigates the performance of established image registration methods for stitching partially overlapping ultrasonic C-scan corrosion maps, with the aim of improving data continuity in phased array ultrasonic testing (PAUT). Three popular feature detectors, KAZE, SIFT, and SURF, are evaluated alongside two extraction methods, SURF descriptor format and Histogram of Oriented Gradients (HOG), on a dataset of 1200 simulated corrosion maps with a 10 mm initial backwall thickness. Each corroded map is divided into two overlapping C-scan strips (100 × 200 pixels), simulating inspection scenarios with overlap ranging from 1 to 50 pixels and misalignments up to 20° rotation. The analysis incorporates realistic acquisition imperfections, including signal noise (0–2 mm) and encoder skips.

Results show that KAZE outperforms SIFT and SURF, particularly under noisy conditions, achieving stitching success rates up to 98% when overlaps exceed 10 elements. In ideal conditions, all detectors maintain high performance (90%–95%), but noise and rotational misalignment significantly degrade the results. The two extraction methods are similar for large depth variations, but when depth variation is small (

\leq

1 mm), SURF is more effective at small overlaps (

\leq

20 elements), while HOG exhibits greater robustness at larger overlaps. Among all tested inspection errors, rotational misalignment had the greatest negative impact on stitching accuracy, followed by noise, with encoder skips showing minimal effect.

These findings support the integration of advanced feature-based registration techniques into PAUT data processing workflows, enabling improved corrosion mapping and defect characterisation across multiple scans.

本研究研究了现有图像配准方法的性能，用于拼接部分重叠的超声c扫描腐蚀图，目的是提高相控阵超声检测（PAUT）中的数据连续性。在1200张初始后壁厚度为10mm的模拟腐蚀图数据集上，对KAZE、SIFT和SURF三种流行的特征检测器以及SURF描述符格式和定向梯度直方图（HOG）两种提取方法进行了评估。每张腐蚀图被分成两个重叠的c扫描带（100 × 200像素），模拟检查场景，重叠范围从1到50像素，不对齐可达20°旋转。分析包含现实的采集缺陷，包括信号噪声（0-2毫米）和编码器跳过。结果表明，KAZE优于SIFT和SURF，特别是在噪声条件下，当重叠超过10个元素时，拼接成功率高达98%。在理想条件下，所有探测器都保持高性能（90%-95%），但噪声和旋转不对准会显著降低结果。两种提取方法在深度变化较大时相似，但当深度变化较小（≤1 mm）时，SURF在小重叠处（≤20个元素）更有效，而HOG在大重叠处表现出更强的鲁棒性。在所有测试的检测误差中，旋转不对准对拼接精度的负面影响最大，其次是噪声，编码器跳过的影响最小。这些发现支持将先进的基于特征的注册技术集成到pat数据处理工作流程中，从而改进了跨多次扫描的腐蚀映射和缺陷表征。

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引用次数: 0

A steady-state wavefield polarity-aware U-Net for ultrasonic guided waves depth-resolved imaging 用于超声导波深度分辨成像的稳态波场极性感知U-Net

IF 4.5 2区材料科学 Q1 MATERIALS SCIENCE, CHARACTERIZATION & TESTING

Ndt & E International

Pub Date : 2026-03-01 Epub Date: 2025-11-15 DOI: 10.1016/j.ndteint.2025.103597

Xuan Li , Lishuai Liu , Jiang Lu , Yuncheng Zhang , Dazhi Cong , Yanxun Xiang

The laser scanning full wavefield capture (LSFWC) technique enables rapid acquisition of two‐dimensional maps of local velocity variations of ultrasonic guided waves (UGWs), thereby facilitating quantitative spatial visualization of damage in thin‐walled structures. However, this technique faces a trade-off among spatial resolution, the accuracy of damage estimation, and detection efficiency: the spatial sampling rate influences the limit of velocity estimation, whereas increasing the sampling rate renders the full wavefield data acquisition extremely time-consuming. To tackle these difficulties, we propose a U-Net based imaging approach to reconstruct high-quality depth-resolved images from steady-state wavefield polarity (SSWP) of spatial sub-Nyquist sampled UGWs. The developed SSWP-aware U-Net can automatically segment the wavefield, extract local phase information, and perform encoding and decoding to establish approximate nonlinear mapping between wavefield and spatial distribution of UGWs velocity variations. The selection of SSWP as input features greatly accelerates the acquisition of the training dataset, and further enhances the robustness and generalization ability of U-Net trained on simulated dataset. We experimentally compared the proposed imaging method to wavenumber estimation methods. The results demonstrated that the proposed SSWP-aware U-Net is significantly superior to traditional methods in terms of image reconstruction quality and defect depth resolution especially with local spatial sub-Nyquist sampling.

激光扫描全波场捕获（LSFWC）技术能够快速获取超声导波（ugw）局部速度变化的二维地图，从而促进薄壁结构损伤的定量空间可视化。然而，该技术面临着空间分辨率、损伤估计精度和检测效率之间的权衡：空间采样率影响速度估计的极限，而增加采样率使得全波场数据采集非常耗时。为了解决这些困难，我们提出了一种基于U-Net的成像方法，从空间亚奈奎斯特采样的ugw的稳态波场极性（SSWP）重建高质量的深度分辨率图像。开发的感知sswp的U-Net可以自动分割波场，提取局部相位信息，进行编解码，建立波场与ugw速度变化空间分布的近似非线性映射关系。选择SSWP作为输入特征大大加快了训练数据集的获取速度，进一步增强了U-Net在模拟数据集上训练的鲁棒性和泛化能力。我们实验比较了所提出的成像方法和波数估计方法。结果表明，基于sswp感知的U-Net在图像重建质量和缺陷深度分辨率方面明显优于传统方法，特别是在局部空间亚奈奎斯特采样方面。

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引用次数: 0

Quantitative evaluation of the reliability of hybrid corrosion inspection and monitoring approaches 混合腐蚀检测与监测方法可靠性的定量评价

IF 4.5 2区材料科学 Q1 MATERIALS SCIENCE, CHARACTERIZATION & TESTING

Ndt & E International

Pub Date : 2026-03-01 Epub Date: 2025-08-25 DOI: 10.1016/j.ndteint.2025.103527

Yifeng Zhang, Frederic Cegla

Conventional ultrasonic approaches for corrosion surveillance such as large-scale C-scans and continuous localised monitoring face inherent limitations in either temporal resolution or spatial coverage. Recent advances in sensor technology and low-cost autonomous robotics enables a hybrid approach that combine their strengths. However, critical questions remain about optimising such approaches, including determining the optimal inspection intervals, spatial coverage, and number of sensors. This study presents a multi-stage framework that addresses these challenges through integrated modelling: degradation simulation for spatiotemporal evolution of component surfaces, physics-based surrogate models for ultrasonic thickness measurements, data subsampling to replicate inspection and monitoring procedures, and reliability assessments against surveillance targets. Through Monte Carlo simulations on synthesised data calibrated to field measurements, we demonstrate the potential benefits of the hybrid strategy. Results show that strategic sensor placement and periodic repositioning can enhance reliability while reducing coverage requirements and extending inspection intervals. Importantly, this framework provides quantitative guidance for corrosion surveillance planning and can be adapted to different degradation phenomena across various asset types.

传统的超声波腐蚀监测方法，如大规模c扫描和连续的局部监测，在时间分辨率或空间覆盖方面都存在固有的局限性。传感器技术和低成本自主机器人技术的最新进展使结合其优势的混合方法成为可能。然而，优化这些方法的关键问题仍然存在，包括确定最佳检查间隔、空间覆盖范围和传感器数量。本研究提出了一个多阶段框架，通过集成建模来解决这些挑战：组件表面时空演变的退化模拟，超声厚度测量的基于物理的替代模型，复制检查和监测过程的数据子采样，以及针对监视目标的可靠性评估。通过对现场测量校准的综合数据进行蒙特卡罗模拟，我们证明了混合策略的潜在优势。结果表明，传感器的策略性放置和周期性重新定位可以提高可靠性，同时降低覆盖要求和延长检测间隔。重要的是，该框架为腐蚀监测规划提供了定量指导，可以适应不同资产类型的不同退化现象。

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引用次数: 0