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Image Recognition Method for Defect on Coke with Low-quality Coal

机译:劣质煤焦炭缺陷的图像识别方法

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The image recognition method was proposed to quantify non-adhesion grain boundaries which were considered as a factor of coke strength besides pores, and the correlation between coke strength and the amount of defects evaluated by the method was investigated in comparison with the one by the marking method. Coke with low-quality coal was fractured by a diametral-compression test, and the fracture cross-sections were observed by a scanning electron microscopy (SEM) and a 3D laser scanning microscope (LSM). The marking method and image recognition method were applied to SEM and LSM images, respectively. As a result, the fracture strength measured by the diametral-compression test was linearly decreased with an increase in blending ratio of low-quality coal. In the marking method, most non-adhesion grain boundaries were not detected up to 50% in the blending ratio, and the boundaries increased sharply from 50 to 100% in the blending ratio. On the other hand, in the recognition method, the defects which were composed of both pores and non-adhesion grain boundaries, increased linearly with the blending ratio, and the amount of defects corresponded to coke strength. Therefore, the image recognition method is expected as the quantification technique of defects decreasing coke strength.
机译:提出了一种图像识别方法来量化非粘附性晶界,该非粘附性晶界被认为是除了孔隙之外的焦炭强度的一个因素,并且与通过标记的缺陷相比,研究了焦炭强度与该方法评估的缺陷量之间的相关性。方法。通过直径压缩试验使劣质煤的焦炭断裂,并通过扫描电子显微镜(SEM)和3D激光扫描显微镜(LSM)观察断裂截面。标记方法和图像识别方法分别应用于SEM和LSM图像。结果,通过径向压缩试验测得的断裂强度随着劣质煤的混合比的增加而线性降低。在标记方法中,在掺混率高达50%时,未检测到大多数非粘附性晶界,并且掺混率从50%急剧上升至100%。另一方面,在识别方法中,由孔和非粘附性晶界构成的缺陷随着混合比线性增加,并且缺陷的数量对应于焦炭强度。因此,期望图像识别方法作为降低焦炭强度的缺陷的量化技术。

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