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Principal Component Analysis for Physical Properties of Electric Arc Furnace Oxidizing Slag

机译:电弧炉物理性质氧化渣的主成分分析

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In this study, the principal component analysis (PCA) was used to analyze and classify the electric arc furnace oxidizing slag based on physical properties. The results indicated that about 91.44% information could be explained using the previous four PC. The Los Angeles abrasion test (LAAT) and loss of sodium sulfate soundness test (LSSST) mainly contributed to the first PC, meanwhile the saturated surface-dry specific gravity (SSDSG) contributed mainly to the second PC. The significant physical properties of EAF slag including LAAT, LSSST, and SSDSG could be identified according to PCA. According to the two dimension classification using PC1 and PC2, the 60 samples could be approximately classified into two groups. They could be also classified into two groups in three dimension classification.
机译:在该研究中,主要成分分析(PCA)用于根据物理性质分析和分类电弧炉氧化渣。结果表明,可以使用前四个PC解释约91.44%的信息。洛杉矶磨损试验(LAAT)和硫酸钠声音试验(LSSST)主要导致第一PC,同时,饱和表面干特异性重力(SSDSG)主要贡献到第二台PC。可以根据PCA识别包括LAAT,LSSST和SSDSG的EAF渣的显着物理性质。根据使用PC1和PC2的两个维度分类,60个样本可以大致分为两组。他们还可以分为三个维度分类。

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