An Infrared Imaging System for Compositional Analysis of Iron Ore

Abstract

The Infrared (IR) imaging technique is usually used in industries for predictive maintenance and non-destructive evaluation of thermal and mechanical properties. Venturing into a completely different application of IR imaging, we present a fast and low cost technique for compositional analysis of iron ores, taking into account the variation in thermal absorptivity of the ore constituents. The technique primarily consists of selection of iron ores with Fe compositions ranging from 58 to 67 wt% and alumina (Al2O3 ) from 1.0 to 7.5 wt%, crushing the ores up to the particle size range around 10 mm. A fixed quantity of crushed iron ore particles are uniformly heated using a microwave oven, for a time period sufficient to create a difference in infrared emission between the ore particles. The IR image of the heated ores is captured and their average temperature is obtained. The average temperature of the heated ore particles varies with the alumina content in the ores. The higher the alumina content in the ores, lower is the average temperature. Through IR imaging of ores with varying alumina, a calibration curve is generated which correlates the average temperature of the ores with their corresponding alumina content obtained through chemical analysis. The alumina content in the unknown iron ore samples can be predicted from the calibration curve. This IR imaging technique for compositional analysis of ores can be considered as a substitute for the more prevalent chemical analysis method which is time-consuming and cumbersome. Implementation of this technique in beneficiation process in the mines would lead to more systematic and improved decision making for effective blend planning and defect reduction. Additionally, real time analysis of feed grade to the plant operators would help in effective plant operation to achieve targeted output in terms of alumina percentage and yield.