Title of article :
Modelling SAG milling power and specific energy consumption including the feed percentage of intermediate size particles
Author/Authors :
Silva، نويسنده , , M. and Casali، نويسنده , , A.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2015
Pages :
6
From page :
156
To page :
161
Abstract :
Comminution, particularly milling, is on average the largest consumer of energy in mining. Actual comminution circuits consist in most of the cases in coarse crushing, SAG milling, pebble crushing and secondary ball milling. In these circuits the SAG mill is the largest energy consumer. In many engineering projects either a power equation and/or a specific energy equation are used for the designing of these mills but not always with acceptable results. In general these equations are used to predict power consumption as a function of mill size, level and density of the internal charge and % of critical speed. Almost none of these equations (with the notable exception of the Morrell’s model) consider explicitly the effect that the feed particle size has on the mill performance, particularly on the power and on the specific energy consumption of the mill. To address this fact new models are developed in this work able to predict power or specific energy consumption, including the usual design variables, but adding a variable that represents the feed size distribution. Operational data from 4 grinding circuits corresponding to 3 Chilean copper concentration plants are used and the % −6″ +1″ (−152 +25 mm) is selected as independent variable. The results indicate that both models are able to estimate the required variables for all data sets. In the first model (power equation) the average error obtained was 3.7% and in the second model (specific energy) the average error was 6.8%. These models would be useful for performance optimisation of the test case mills and should be fitted (parameters values) again for other mills.
Keywords :
sag milling , Power modelling , Especific energy modelling , SAG mills operation data
Journal title :
Minerals Engineering
Serial Year :
2015
Journal title :
Minerals Engineering
Record number :
2277838
Link To Document :
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