Optimization of Coal Production Based on the Modeling of the Jig Operation

Abstract

This paper presents the jig operating properties of the selected final parameters of the hard coal concentrate. The quality parameters of the product, such as the yield and ash content, were evaluated in terms of the technical and hydrodynamic parameters of the jig’s operation. The research program included a series of experiments in which the efficiency and the amount of hutch water were changed. The variables selected and analyzed were divided into two categories, i.e., one related to the characteristics of the concentrate produced, and the other to the characteristics of the jig operation. Models were built for narrowed particle size fractions based on concentrate yield and ash content in the concentrate. In addition, a multidimensional analysis was performed, considering variables such as machine throughput, which was determined by the flow rate of the material, the amount of hutch water, the quality of the concentrate, and the amount of concentrate, as well as the accuracy of the jig operation expressed by the imperfection. Two main parameters were taken into account for modeling the operation to examine their significance of influence on the final responses in terms of the possibility of adjusting the value of independent settings of the jig operation. The presented approach to modeling the operation of the jig can be extended by considering the impact of other parameters, taking into account the variability of the final effect, as long as it is allowed under the industrial conditions of machine operation and the assumed production requirements. The approach presented in this paper is a new technique, which was not found in the literature.

Signal Processing from the Radiation Detector of the Radiometric Density Meter Using the Low-Pass Infinite Impulse Response Filter in the Measurement Path in the Coal Enrichment Process Control System

“…This makes it possible to improve the dynamic properties of the radiometric density meter while maintaining its accuracy at the required level by making the parameter a of the filter Equation ( 9) dependent on the time derivative of the medium density in such a way that for a high rate of change of the medium density the coefficient a will have a small value, and for a small value of dρ/dt a large value. Knowing the parameters of the model (1) for one cycle, the derivative of density with respect to time (10) in this cycle can be determined. In order to use the derivative of the density of the medium, determined for one cycle, to filter the signal from the density meter in subsequent cycles, it is advantageous to standardize it in the range [0, 1].…”

“…value. Knowing the parameters of the model (1) for one cycle, the derivative of density with respect to time (10) in this cycle can be determined. In order to use the derivative of the density of the medium, determined for one cycle, to filter the signal from the density meter in subsequent cycles, it is advantageous to standardize it in the range [0, 1].…”

“…In this process, the grains are distributed according to their density as a result of cyclical water movement up and down, causing adequate loosening of the material, and then stratification of grains due to differences in the speeds of their falling depending on the density and size. A properly conducted process ensures stratification of the material in such a way that the layers consisting of greater density grains are in the lower part, and the grains with lower density form the upper layers [10,11]. In the automatic control system of the coal enrichment process usually the basic sensor indicating the position of material layer with a selected density is a metal float.…”

Research on prediction of coal water medium separation effect based on multi-models

“…Gravity separation is one of the main methods used for coal separation. It includes heavy medium [ 2 , 3 ], water medium [ 4 , 5 ], and air medium [ 6 , 7 ] separation. The water-medium separation methods include jigging separation [ 8 ], coarse slime interference bed separation (TBS) [ 9 ], and the spiral separation technique [ 10 ].…”

“…Niedoba et al [ 15 ] used the Kruskal-Wallis and Friedman statistical tests, to analyze the effects of the combination of the hutch water amount, the system capacity, and the particle characteristics on clean coal yield and ash in jig separation, to optimize the outcome. Surowiak et al [ 16 ] used the throughput and hutch water parameters of the jigger as independent variables and built a model to evaluate the yield and ash of the jig products to determine the optimal area of these two parameters for the required quality. Kumar and Venugopal [ 17 ] considered the coal particle size, jig bed height, and sorting time as process variables to analyze their effect on the performance of the jig in terms of the clean coal ash.…”