Texture analysis of the microstructure of internal curing concrete based on image recognition technology

Guo, Lixia; Wang, Weikai; Zhong, Lijuan; Guo, Lei; Zhang, Fangfang; Guo, Yuhang

doi:10.1016/j.cscm.2022.e01360

Cited by 5 publications

(6 citation statements)

References 27 publications

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“…The hydrated products, CSH and MSH together can be observed as a dense non crystalline matrix. In the image of DC40, more flaky nature of hydrated product of dolomite can be observed [29][30][31][32][33][34]. The unreacted dolomite powder crystals can be seen in the images of DC50, DC60 and DC70.…”

Section: Sem Analysismentioning

confidence: 95%

Evaluation of strength of self-compacting concrete having dolomite powder as partial replacement for cement

Kumar,

Prabaghar

2023

Res. Eng. Struct. Mat.

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Now a day, the utilization of self-compacting concrete (SCC) has become popular in creating RC structures. Apart from self-compaction, SCC has got many advantages such as excellent flow ability, filling ability, smooth finish of surface, ease of work etc. The use of waste material in concrete is the area of having scope for researchers for many years. Use of waste material reduces the consumption of cement by construction sector. In this present experimental work, dolomite powder is used as fractional replacement material for cement. The cement in the SCC is replaced by dolomite at fractions of 10%, 20%, 30%, 40%, 50%, 60%, and 70%. Fly ash is also added to the mix at constant fraction of 18% of the cement. The strength of SCC is assessed by performing compression test, splitting tension test and bending test. The test results showed that the use of dolomite powder in SCC is advantageous up to 20% replacement fraction. It is also observed that the strength of DC40 mix (i.e the mix having Dolomite at 40% of cement) is almost equal to the strength of normal SCC. Even at 70% replacement level, the strength of SCC having dolomite achieved is 25 MPa. SEM images are analyzed to identify the spread of hydrated products.

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Section: Sem Analysismentioning

confidence: 95%

Evaluation of strength of self-compacting concrete having dolomite powder as partial replacement for cement

Kumar,

Prabaghar

2023

Res. Eng. Struct. Mat.

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“…The gray-level co-occurrence matrix has many characteristic parameters. Haralick et al defined 14 gray-level co-occurrence matrix parameters for texture analysis [9], of which entropy is a parameter representing the texture thickness, complexity, and the amount of information contained in the image, and angular second moment is a parameter representing the uniformity of gray pixel distribution.…”

Section: Evaluation Characteristic Parametersmentioning

confidence: 99%

Evaluation of Gasket Surface Contact Stress Uniformity Based on Gray-Level Co-Occurrence Matrix

et al. 2022

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Due to the high demand for compression recovery tests of metal gaskets, it is difficult to provide and evaluate uniform stress on metal gaskets. To effectively evaluate the uniformity of surface stress on a metal gasket, we propose a method of evaluating gasket surface stress based on gray-level co-occurrence matrix theory. Angular second moment and entropy are selected as the main characteristic parameters, and the evaluation indexes (f1 and f2) are proposed. The analysis is based on finite element calculation under different parameters of a gasket test rig. The angular second moment and entropy curve of the stress distribution cloud map are drawn according to the result of finite element calculation. The results show that the method can evaluate the uniformity of stress distribution. The best parameters of the gasket testing rig are obtained by analyzing the uniformity evaluation index. The method can realize rapid comparison and accurate evaluation of the gasket surface stress.

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“…Researchers have proposed several methods to identify defects in concrete structures, which require manual processing to extract defect features from images, including sample feature representation based on image grayscale statistical distribution (Guo et al, 2022), threshold segmentation methods (Kim et al, 2017), and traditional machine learning methods (Hsieh and Tsai, 2020). These methods can obtain the size and distribution of defects, however, most of them are through pixel changes and lack of sufficient extraction of the background and features of the defect information in images.…”

Section: Introductionmentioning

confidence: 99%

Image-based automatic multiple-defect detection of urban utility tunnel using UUTNet

Sun,

Hou,

et al. 2024

Advances in Structural Engineering

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In-service urban utility tunnels (UUT) suffer from cracks, corrosion, and leakage defects, which rises the chance of major accidents. However, prevailing detection methods for UUT remain reliant on manual inspection and subjective judgment, or traditional image processing technologies, such methods may not be able to obtain accurate defect information. This study proposes a novel and effective network called UUTNet based on the constructed UUT dataset for defects detection. Considering that the UUT defects has a certain distribution correlation, the attention module is introduced to the Pyramid Scene Parsing Network to capture the relation. By adding the hybrid dilated convolution after the feature extraction layer, the receptive field is expanded to further extract global and local features. The performance of UUTNet was evaluated based on the metrics MIoU, F1-score, Accuracy, and robustness. Comparative experiments were conducted, and the results showed the UUTNet achieved the best detection performance, achieving 0.7615 MIoU, 0.9806 Accuracy and 0.8012 F1-score. The MIoU was further improved to 0.7847 by utilizing the Bayesian optimization. Three extreme inspection scenes, including uneven illumination, high brightness, and obstacle interference, were applied to validate model robustness. The proposed method offers robust technical assistance for detecting defects in the UUT and precisely assessing the distribution and extent of these defects.

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Texture analysis of the microstructure of internal curing concrete based on image recognition technology

Cited by 5 publications

References 27 publications

Evaluation of strength of self-compacting concrete having dolomite powder as partial replacement for cement

Evaluation of strength of self-compacting concrete having dolomite powder as partial replacement for cement

Evaluation of Gasket Surface Contact Stress Uniformity Based on Gray-Level Co-Occurrence Matrix

Image-based automatic multiple-defect detection of urban utility tunnel using UUTNet

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