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首页> 外文期刊>International Journal of Applied Pattern Recognition >New approaches of three-dimensional image processing applied to the study of lightweight mortars with EVA aggregates and piassava fibres
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New approaches of three-dimensional image processing applied to the study of lightweight mortars with EVA aggregates and piassava fibres

机译:三维图像处理的新方法应用于研究带有EVA骨料和木薯纤维的轻质砂浆

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摘要

Civil construction is an alternative for the reuse of industrial discarded materials. The ethylene-vinyl acetate's residue as an aggregate, generates light materials with interesting thermal and acoustic properties. However, adding EVA reduces the material strength. To soften this effect, natural fibres like piassava can be added. This work proposes a methodology of three dimensional tomographic image analysis for the characterisation of lightweight mortars reinforced with piassava fibres. For this, several image features were calculated using different algorithms approaches focusing on the memory efficiency, the main handicap of three-dimensional image analysis. The methodology identified the EVA grains, the fibres and the pores, being insufficient collected information for the cracks identification. Also, it was possible to verify the fibre action as reinforcement. Regarding the algorithm performance analysis, the two-passage approaches were better, being the memory focused approach, the only one that can work with very big 3D images.
机译:土建是工业废料再利用的替代选择。乙烯-乙酸乙烯酯的残留物为聚集体,可产生具有令人感兴趣的热和声特性的轻质材料。但是,添加EVA会降低材料强度。为了减轻这种影响,可以添加诸如piassava的天然纤维。这项工作提出了三维断层图像分析的方法,用于表征由木薯纤维增强的轻质砂浆的特性。为此,使用不同的算法方法来计算几个图像特征,这些算法的重点是存储效率,这是三维图像分析的主要障碍。该方法识别出EVA晶粒,纤维和孔,这些信息不足以识别裂纹。同样,可以验证纤维作为增强材料的作用。关于算法性能分析,两遍方法更好,它是以内存为中心的方法,它是唯一可以处理非常大的3D图像的方法。

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