The development of dynamic models for a dense medium separation circuit in coal beneficiation

Abstract

a b s t r a c tOften the most difficult step in establishing a control system is the development of a suitable dynamic process model. As such a model is not available elsewhere, a first principle dynamic mathematical model was developed for a coal dense medium separation circuit. Each unit operation was modelled individually and then integrated together to form a complete non-linear state-space model for the circuit. This model was used to simulate the process and it was validated using real process data derived from a plant experiment.When developing models from first principles, it is necessary to estimate the model parameters. These parameters, specifically for non-linear state-space relationships, require a unique solution. A parameter identifiability method was used to show that the non-linear dynamic models developed have unique parameters for a specific set of input-output data.

Coal dense medium separation dynamic and steady-state modelling for process control

“…The objective of the DMS plant operation is to produce coal product within a minimum quality specification and maximum possible yield (England et al, 2002). Meyer and Craig (2010) have indicated that coal DMS plants do not typically operate at steady state and that setpoint changes should be tracked appropriately in terms of ash content and yield. Almost all DMS plants are only automatically controlled at the regulatory control level in terms of medium density and ore feed rate and there are significant financial implications if the average yield and ash content of product coal can be controlled and optimised.…”

“…Dynamic process models for the coal DMS process are limited in the available published literature (Meyer and Craig, 2010). Steady-state models developed by Napier-Munn (1991) cannot be used for process control purposes due to the need for time-varying process variables.…”

“…This linear relationship results in the model only working within a narrow medium density band and can be viewed as a limitation. The dynamic models developed by Meyer and Craig (2010) are detailed in such a way that they can be used to simulate time-varying coal product quality and throughput. These models are based on first principles using conservation of mass and mass of components (Stephanopoulos, 1984) and can be used for simulating and validating process control strategies for DMS circuits.…”

“…These models are based on first principles using conservation of mass and mass of components (Stephanopoulos, 1984) and can be used for simulating and validating process control strategies for DMS circuits. The models developed in Meyer and Craig (2010) were validated by comparing their responses to experimental data obtained from a fine coal dense medium cyclone (DMC) circuit. These data were generated from step changes in medium density, and the resulting changes in product ash content were carefully observed.…”

“…These data were generated from step changes in medium density, and the resulting changes in product ash content were carefully observed. This paper will focus on using the dynamic process models develop by Meyer and Craig (2010) for a fine coal DMC and identify and validate them using throughput and yield for a coarse DMC circuit. System identification (Ljung, 1987) is used to identify the developed models.…”