Principal Component Analysis for Physical Properties of Electric Arc Furnace Oxidizing Slag
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.
Bale V. Reddy, Shishir Kumar Sahu, A. Kandasamy and Manuel de La Sen
L. Chen and T. Y. Pai, "Principal Component Analysis for Physical Properties of Electric Arc Furnace Oxidizing Slag", Applied Mechanics and Materials, Vol. 627, pp. 323-326, 2014