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| 基于相干加权融合的混凝土缺陷检测全聚焦成像技术研究 |
| Research on Full-Focus Imaging Technology for Concrete DefectsBased on Coherent Weighted Fusion |
| 投稿时间：2025-08-02 修订日期：2025-12-18 |
| DOI： |
| 中文关键词: 全聚焦成像 混凝土缺陷 相干加权融合 成像分辨率 信噪比 |
| 英文关键词: Total Focusing Method Concrete Defects Coherent Weighted Fusion Imaging Resolution Signal-to-Noise Ratio |
| 基金项目:中国水科院基本科研业务费项目(SM0145B042021) |
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| 中文摘要: |
| 混凝土是由骨料、水泥浆体等多相异质组分构成的复合材料，其内部存在的复杂声阻抗界面虽是超声检测缺陷的物理基础，但同样也会引发强烈的散射噪声和显著的超声能量衰减特性，使得基于超声检测的成像质量仍面临诸多限制。其中，全聚焦成像（TFM）技术虽能通过全矩阵数据（FMC）采集提升分辨率，但在混凝土这类强散射介质中仍受噪声和伪像干扰。为进一步提高全聚焦成像质量，本文提出了一种基于相干加权融合（CWF）的全聚焦成像算法（TFM）。该方法旨在最大化利用全矩阵数据（FMC）中所包含的散射场，以扩大相干与非相干信号间的差异，从而增强最终成像分辨率和缺陷可辨识度。混凝土细观模型数值模拟和实验结果表明，CWF-TFM全聚焦优化算法能够有效抑制部分噪声和伪像，提高纵向分辨率，使缺陷区域信号更加集中。在用50 kHz激励信号检测单裂缝缺陷时，信噪比较传统TFM提高30.0%；检测单孔洞缺陷时，信噪比较传统TFM提高32%；检测多缺陷时，信噪比较传统TFM提高23%。该成果突破了传统TFM在混凝土缺陷检测中的模态局限性，显著提升了图像信噪比以及缺陷可辨识度，为高分辨率超声混凝土缺陷检测提供了新思路。 |
| 英文摘要: |
| Concrete is a composite material composed of multi-phase heterogeneous components such as aggregates and cement paste. While the complex acoustic impedance interfaces within it provide the physical basis of ultrasonic defect detection, they also generate strong scattering noise and significant ultrasonic energy attenuation, imposing considerable limitations on the imaging quality of ultrasound-based detection. Although the total focusing method (TFM) technology can improve the resolution through full matrix capture (FMC) data acquisition, but it remains susceptible to noise and artifacts in strongly scattering media such as concrete. In order to further enhance TFM quality, a TFM algorithm based on coherence weighted fusion (CWF) is proposed. This method aims to maximize the use of the scattered field contained in the FMC data to amplify the difference between coherent and incoherent signals, thereby enhancing the final imaging resolution and defect identifiability. Numerical simulations on a meso-scale concrete model and experimental results show that the proposed CWF-TFM optimization algorithm can effectively suppress certain noise and artifacts, improve the longitudinal resolution, and concentrate signals in defect areas. When using a 50 kHz excitation signal to detect a single crack defect, the signal-to-noise ratio (SNR) is improved by 30.0% compared with traditional TFM. For single void defect detection, the SNR is increased by 32% over traditional TFM. and for multiple defects, the SNR shows a 23% enhancement. This achievement overcomes the modal limitations of traditional TFM in concrete defect detection, significantly improving image SNR and defect identifiability, and provides a new approach for high-resolution ultrasonic detection of concrete defects. |
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