A new on-line method for predicting iron ore pellet quality
© 2015 Taylor & Francis Group, LLC. The Abrasion Index (AI) describes fines generation from iron ore pellets, and is one of the most common indicators of pellet quality. In a typical pellet plant, dust is generated during the process and then captured. Can the dust be measured and used to predict AI? In this paper, the feasibility of using airborne dust measurements as an indicator of AI is investigated through laboratory tests and using data from a pellet plant. Bentonite clay, polyacrylamide and pregelled cornstarch contents, and induration temperature were adjusted to control the abrasion resistance of laboratory iron ore pellets. AI were observed to range from approximately 1% to 12%. Size distributions of the abrasion progeny were measured and used to estimate quantities of PM < inf> 10 (particulate matter with aerodynamic diameter less than 10 μm) produced during abrasion. A very good correlation between AI and PM < inf> 10 (R < sup> 2 = 0.90) was observed using the laboratory pellets. Similarly, a correlation was observed between AI and PM measured in the screening chimney at a straight-grate pelletization plant in Brazil, with an R < sup> 2 value of 0.65. Thus, the laboratory and industry data suggest that measuring dust generation from fired pellets may be an effective on-line measurement of pellet quality. The data also showed that particulate emissions from pelletization plants may be directly affected by AI.
Mineral Processing and Extractive Metallurgy Review
A new on-line method for predicting iron ore pellet quality.
Mineral Processing and Extractive Metallurgy Review,
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