Abstract:-Based on a dynamical model of the grinding process in closed circuit mills, efficient efforts have been made to optimize PID controllers of cement milling. The process simulation is combined with an autoregressive model of the errors between the actual process values and the computed ones. Long term industrial data have been used to determine the model parameters. The data include grinding of various cement types. The M -Constrained Integral Gain Optimization (MIGO) loop shaping method is utilized to determin… Show more
“…More energy efficient grinding technologies, applied in the grinding of cement, are described comparatively in the paper [6], from the point of view of operating principles, grinding efficiency, specific energy consumption, the production capacity and the quality of the cement obtained. Other papers addressing the theme of milling process with balls dedicated to grinding cement, including its control are [7][8][9][10][11] The present paper presents the results regarding the grinding behaviour of two batches of material (clinker) in a ball mill with its own two-step grinding process: the first one with a ball load, the second with a load of cylindrical metal bodies.…”
This paper presents results regarding the grinding behaviour of two batches of material (clinker) in a ball mill with its own two-step grinding process: the first one with a ball load, the second with a load of cylindrical metal bodies. The first step was performed until the residue R009 has reached aprox.35%, and the second stage until Blaine's specific surface was over 3800 cm2/g. Periodically, at 10-minute intervals, the fineness of the clinker and the specific energy consumption were determined. These consumptions are quantified from the first determination and relates to the weight of the material subjected to grinding (20 kg clinker / from a source), determining the grinding ability of the material.
“…More energy efficient grinding technologies, applied in the grinding of cement, are described comparatively in the paper [6], from the point of view of operating principles, grinding efficiency, specific energy consumption, the production capacity and the quality of the cement obtained. Other papers addressing the theme of milling process with balls dedicated to grinding cement, including its control are [7][8][9][10][11] The present paper presents the results regarding the grinding behaviour of two batches of material (clinker) in a ball mill with its own two-step grinding process: the first one with a ball load, the second with a load of cylindrical metal bodies.…”
This paper presents results regarding the grinding behaviour of two batches of material (clinker) in a ball mill with its own two-step grinding process: the first one with a ball load, the second with a load of cylindrical metal bodies. The first step was performed until the residue R009 has reached aprox.35%, and the second stage until Blaine's specific surface was over 3800 cm2/g. Periodically, at 10-minute intervals, the fineness of the clinker and the specific energy consumption were determined. These consumptions are quantified from the first determination and relates to the weight of the material subjected to grinding (20 kg clinker / from a source), determining the grinding ability of the material.
“…Many contributions have been made in the control of grinding circuits. For instance, reference [3] proposes a dynamical model of the grinding process to tune the PID controllers involved in the cement milling by the loop shaping method.…”
This paper presents the development of a non-linear model predictive controller (NMPC) applied to a closed grinding circuit system in the cement industry. A Markov chain model is used to characterize the cement grinding circuit by modeling the ball mill and the centrifugal dust separator. The probability matrices of the Markovian model are obtained through a combination of comminution principles and experimental data obtained from the particle size distribution (PSD) of cement samples at specific stages of the system. The NMPC is designed as a supervisory controller in order to manage distributed controllers (DCs) installed in the process. Both the model and the controller are validated online through the implementation of the proposed approach in the supervisory control and data acquisition (SCADA) system of an industrial plant. The results show a significant improvement in the performance of the grinding circuit in comparison to the operation of the system without the proposed controller.
“…Some of the challenges facing the cement industries are the high energy demand of production, the continuous increase in fuel prices, process complexity and environmental impact (Atmaca and Yumruta 2014, Tsamatsoulis 2014, Kaddatz et al 2013, Gartner and Macphee 2011, Schneider et al 2011, Mujumdara et al 2007). To address these challenges, there is great interest in optimising the cement production process (Copertaro et al 2015, Utlu et al 2006.…”
Cement is one of the most used building materials in the world. The process of cement production involves numerous and complex reactions that occur under different temperatures. Thus, there is great interest in the optimization of cement manufacturing. Clinker production is one of the main steps of cement production and it occurs inside the kiln. In this paper, the dry process of clinker production is analysed in a rotary kiln that operates in counter flow. The main phenomena involved in clinker production is as follows: free residual water evaporation of raw material, decomposition of magnesium carbonate, decarbonation, formation of C 3 A and C 4 AF, formation of dicalcium silicate, and formation of tricalcium silicate. The main objective of this study was to propose a mathematical model that realistically describes the temperature profile and the concentration of clinker components in a real rotary kiln. In addition, the influence of different speeds of inlet gas and solids in the system was analysed. The mathematical model is composed of partial differential equations. The model was implemented in Mathcad (available at CCA/UFES) and solved using industrial input data. The proposal model is satisfactory to describe the temperature and concentration profiles of a real rotary kiln.
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