Expert system based adaptive dynamic matrix control for ball mill grinding circuit

Chen, Xisong; Li, Shihua; Zhai, Junyong; Li, Qi

doi:10.1016/j.eswa.2007.10.008

Cited by 38 publications

(20 citation statements)

References 17 publications

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“…The experience of the operators is essential for designing optimal scheduling of the expert system to gather the best operational practices of different work shifts. It is worth mentioning that the system can improve over time, either with new operational maneuvers or with additional schedules, similar to what has been seen in three different studies (References [16][17][18][19]). The contribution of this work is that it applied methodological techniques for the development of the knowledge base in an industrial application of a multivariate and multiparametric process.…”

Section: Introductionsupporting

confidence: 70%

Design and Evaluation of an Expert System in a Crushing Plant

et al. 2018

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This document presents a proposal for designing an expert system in the Gabriela Mistral Division’s crushing plant belonging to Codelco (Chile) with the objective of maximizing stacked tonnage, allowing the improvement of operational variables that directly interact with the crushing process. In addition, this study considers the impact that occurs in both the process and operational continuity regarding the standardization of the system. In the first stage, a survey and analysis of historic operation data was carried out, which allowed the definition of benchmarking indicators. Subsequently, both modalities of operation were compared, monitoring processed tonnage and detentions related to operational failures. As a result, significant differences were observed in the performance of the critical line operating with expert control, with a 55% reduction in the detentions referred to operational failures. Added to this is the benefit of low cost and improved quality as the control provides an analysis of the variables in reduced time intervals, which is superior to human control.

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Section: Introductionsupporting

confidence: 70%

Design and Evaluation of an Expert System in a Crushing Plant

et al. 2018

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“…The difficulty of determining the fill level of the mill is revealed by the complexity of the control of the grinding process, specifically in the case of the ball mill type [4], [13][14][15], [17], [19], [21]. Two factors contribute largely to this: the impossibility of siting sensors inside of the mill to provide halfway information between the input and output of the material [4], [13]; and the huge difficulty in obtaining an accurate mathematical modeling of the grinding process, which is strongly affected by the complexity of its dynamical characteristics (the movement of the material within the drum, the size distribution of the ore particles, jams of material, the rotating speed of the mill, etc.)…”

Section: Ball Mills Fill Level Monitoringmentioning

confidence: 99%

Electric motors monitoring: An alternative to increase the efficiency of ball mills

Melero¹,

Cano²,

Norniella³

et al. 2014

REPQJ

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Ball mills can be frequently found in ore grinding facilities. These machines show high energy consumption together with a low efficiency. As a consequence, even a small improvement on the performance of the grinding process can have a huge impact in the operating costs of the plant and in the optimization of energy resources. One of the reasons for this low efficiency rate is the difficulty of identifying the filing level, and as a consequence, the difficulty of operating the mill at the optimum filing condition. Through an extensive bibliographic review, this work attempts to reveal the interesting possibilities that motor monitoring techniques can have in improving the efficiency of ball mills

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“…In the recent years there is still much research on the control strategy for ball mill [1][2][3][4][5][6][7][8][9], such as decentralized PID [1], decoupling control [2,3], fuzzy control [4], self-optimizing control [5,6], predictive control [7], neuronal control [2], and some other combined control algorithm [8,9]. Some of these control strategies are applied in industry, but none of them can occupy the dominant position.…”

Section: Introductionmentioning

confidence: 99%

Loop priority based decentralized control for coal ball mill system

Luo

Liu

Jia

et al. 2010

2010 8th World Congress on Intelligent Control and Automation

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Coal ball mill pulverizing system is a multipleinput multiple-output (MIMO) system characterized with strong couplings and disturbances. In the coal ball mill control system, the three loops possess different dynamics with remarkable lag times. In this paper, we proposed a mixed control scheme based on loop priority (namely the outlet temperature loop, the inlet pressure loop, the pressure difference loop) considering the principle of the safe-stability-quality. The outlet temperature loop employees the feedforward compensation to suppress the interaction from the other two loops; the inlet pressure loop uses the disturbance observer based structure to eliminate internal and external disturbances because the characteristics of the fast response from recycling air flow rate to the inlet pressure is fit to cancel the estimated disturbances; The pressure difference loop controller is designed based on the dominant internal disturbance since it has the lowest priority. The three loop controllers are all in the form of two-degrees-of-freedom PID in order to get a better trade-off between set-point tracking and disturbance rejection. The proposed approach can maintain stable operation of the ball mill, and it is readily available to industrial practitioners and DCS software. Simulation results demonstrate the effectiveness of this control strategy.Index Terms -Multivariable control system, loop priority, ball mill, decentralized control, PID control.

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Expert system based adaptive dynamic matrix control for ball mill grinding circuit

Cited by 38 publications

References 17 publications

Design and Evaluation of an Expert System in a Crushing Plant

Design and Evaluation of an Expert System in a Crushing Plant

Electric motors monitoring: An alternative to increase the efficiency of ball mills

Loop priority based decentralized control for coal ball mill system

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