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基于图像识别的低密度礁灰岩单轴抗压强度试验研究

Experimental Research into the Uniaxial Compressive Strength of Low-Density Reef Limestone Based on Image Recognition.

作者信息

Wei Xiaoqing, Luo Yi, Tao Yuhang, Li Xinping, Meng Fei

机构信息

Sanya Science and Education Innovation Park, Wuhan University of Technology, Sanya 572024, China.

School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, China.

出版信息

Materials (Basel). 2023 Aug 4;16(15):5465. doi: 10.3390/ma16155465.

DOI:10.3390/ma16155465
PMID:37570169
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10420266/
Abstract

Low-density reef limestone is widely distributed in tropical oceans; exploring its mechanical properties is of significance to practices in marine foundation engineering. In this research, laboratory experiments on low-density reef limestones with two different types of porous structures were conducted using image recognition methods to study the special mechanical properties of low-reef limestone. S¯ was defined as the parameter quantifying the pore geometry, and the calculation method of S¯ was optimized based on image recognition data. Finally, the influencing factors of uniaxial compressive strength (UCS) of low-density reef limestone were analyzed, and a modified formula considering pore structure was proposed. The results indicate the following: Image recognition methods were used to determine feasibility and convenience of capturing 2D pore geometric information of specimens. The optimization method of S¯ is conducive to improving automatic image recognition accuracy. Low-density reef limestones with different porous structures show small difference in porosity and density, while they exhibit large differences in pore sizes and UCS. The UCS of low-density reef limestone is found to be jointly influenced by pore structure and density (it increases with the decrease in parameter S¯ and increase in density). The results may provide help for those investigating the mechanical properties of reef limestone and practices in marine foundation engineering.

摘要

低密度礁灰岩广泛分布于热带海洋;探究其力学性能对海洋基础工程实践具有重要意义。本研究采用图像识别方法对两种不同孔隙结构类型的低密度礁灰岩进行室内试验,以研究低礁灰岩的特殊力学性能。定义S¯为量化孔隙几何形状的参数,并基于图像识别数据对S¯的计算方法进行了优化。最后,分析了低密度礁灰岩单轴抗压强度(UCS)的影响因素,并提出了考虑孔隙结构的修正公式。结果表明:采用图像识别方法确定了获取试件二维孔隙几何信息的可行性和便利性。S¯的优化方法有利于提高图像自动识别精度。具有不同孔隙结构的低密度礁灰岩在孔隙率和密度上差异较小,而在孔径和单轴抗压强度上差异较大。发现低密度礁灰岩的单轴抗压强度受孔隙结构和密度的共同影响(随参数S¯的减小和密度的增加而增大)。研究结果可为研究礁灰岩力学性能及海洋基础工程实践提供帮助。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/4079eacf0051/materials-16-05465-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/150a270e5a30/materials-16-05465-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/263200aabb72/materials-16-05465-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/7cebc4164be0/materials-16-05465-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/487966d92b89/materials-16-05465-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/87dd8d09a7ac/materials-16-05465-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/ac8282440f60/materials-16-05465-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/42398125d44d/materials-16-05465-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/614930dd7d02/materials-16-05465-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/4079eacf0051/materials-16-05465-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/150a270e5a30/materials-16-05465-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/263200aabb72/materials-16-05465-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/7cebc4164be0/materials-16-05465-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/487966d92b89/materials-16-05465-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/87dd8d09a7ac/materials-16-05465-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/ac8282440f60/materials-16-05465-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/42398125d44d/materials-16-05465-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/614930dd7d02/materials-16-05465-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10420266/4079eacf0051/materials-16-05465-g009.jpg

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本文引用的文献

1
Quantification of Ceramsite Granules in Lightweight Concrete Panels through an Image Analysis Technique.通过图像分析技术对轻质混凝土板中陶粒颗粒进行量化
Materials (Basel). 2022 Jan 29;15(3):1063. doi: 10.3390/ma15031063.
2
On the use of NIH image J for objective assessment of conjunctival cell and nucleus dimensions of impression cytology samples.利用 NIH 图像 J 对印迹细胞学样本的结膜细胞和细胞核尺寸进行客观评估。
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