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Research on particle stratification inside the model jig wash box based on high-speed dynamic analyzer

ORCID Icon, , , &
Pages 641-652 | Received 25 Oct 2018, Accepted 18 Jan 2019, Published online: 13 Apr 2019
 

ABSTRACT

Jigging is one of the common separation processes in coal beneficiation. The analysis of the impact of jigging operating conditions on the stratification process of the particles inside the model jig wash box has a great guiding significance for improving the performance of the equipment. The experimental results showed that different densities particles exchanging their position in vertical direction mainly occurred during the terminal stage of particle ascending motion and the initial stage of particle descending motion. During this stage, the jig bed was relatively loose, and particles in the bed were conditionally stratified according to their own characteristics (particle size, density, and shape). After the completion of particles stratification, the bed was separated into layers according to particles densities. Material with lower density stayed on top and material with higher density settled at the bottom. Within a bed layer of the same density, the bed was stratified into layers according to particle size. Small particles occupied the upper layer and large particles occupied the lower layer. Experiment of unhindered settling of different particles showed that the terminal settling velocity of large particles was significantly higher than that of small particles of the same density. The terminal settling velocity of large particles with lower density was lower than or equal to that of small particles with higher density. This illustrated that equal settling exists among particles of different densities and sizes. The stratification of materials based on their density could be achieved in a jig, which showed that hindered settling instead of equal setting ratio played a dominant role in jigging process.

Additional information

Funding

This work was supported by the Fundamental Research Funds for Central Universities [grant number 2017XKZD04.

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