Optimal Control of the Sintering Process

Koštial, Imrich; Dorcak, Eubomir; Terpák, Ján

doi:10.3182/20050703-6-cz-1902.01727

Cited by 2 publications

(3 citation statements)

References 6 publications

(5 reference statements)

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“…For the magnesia thermal treatment rotary furnace of SMZ Jelsava, a gas flowing is countercurrent. The heating process model includes a heat transfer between the gas and the material and heat conduction in the material [11]. The following relations were used:…”

Section: Mathematical Model Of the Granular Materials Thermal Treatmentmentioning

confidence: 99%

Simulation Analysis of Preheater Charge to the Rotary Furnace

2015

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Abstract. Mathematical modeling of heat aggregates is one of the fundamental methods of the mathematical modelling research. A mathematical model based on the method of elementary balances was created for the thermal treatment of granular and lumpy materials. The adaptation of the selected aggregate model is based on prior knowledge and experiments. The paper presents an adaptation of the mathematical model for the magnesite processing rotary furnace using the mode of caustic and clinker production. A simulation of the charge preheater impact based on the thin layer principle is implemented into the model. The main advantages of using this type of preheater of rotary furnace are smaller dimensions for a large exchange surface and low pressure losses.

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Section: Mathematical Model Of the Granular Materials Thermal Treatmentmentioning

confidence: 99%

Simulation Analysis of Preheater Charge to the Rotary Furnace

2015

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“…They allow identifying process faults at early stages of their development, determining their causes, and giving recommendations to operating staff to eliminate them. However, according to the literature, insufficient attention was paid to that problem and most articles were devoted to the issues of process simulating and optimizing …”

Section: Introductionmentioning

confidence: 99%

“…However, according to the literature, insufficient attention was paid to that problem and most articles were devoted to the issues of process simulating and optimizing. 5,6 In the articles devoted to diagnostic systems of the agglomeration process, the systems were mainly constructed on the basis of expert systems (ESs). An ES is a system that uses human expertise for decision-making support.…”

Section: Introductionmentioning

confidence: 99%

Diagnostics of sintering processes on the basis of PCA and two‐level neural network model

Egorova

Rudakova

Rusinov

et al. 2017

Journal of Chemometrics

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The application of chemometrics methods to continuous monitoring and diagnostics of sintering process faults for improving iron‐ore sinter quality is considered in the article. The sintering process is among complex multivariate processes. A number of agglomeration process faults have often similar symptoms, resulting in late fault detection by an operator and as a consequence, wrong process control decisions. To support the efficient operative decision making, it is proposed to use the process fault monitoring and diagnostics system. The proposed system uses a two‐level neural network (NN) diagnostic model. The high‐level neural network is used to localize the process faults whereas their reasons are determined by the low‐level neural networks. To reduce essentially the time of HL‐NN training and retraining, the task dimension is preliminarily reduced with the principal component analysis method so that the scores obtained from initial data are fed into high‐level neural network inputs. The use of principal component analysis allowed detection of sintering process faults with T2 and Q statistics. Only upon detecting the fault, a NN diagnostic model starts working to determine the fault reason. The system algorithm provides for special measures to prevent the NN from possible “loss” of the identified fault due to operator's inactivity. To increase the diagnosis depth for controlling fault symptoms that are evident on the sinter cake surface, optical digital cameras are installed and images from them are processed with proposed algorithms on the basis of fuzzy clusterization to take into account uncertainties in the initial information.

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Optimal Control of the Sintering Process

Cited by 2 publications

References 6 publications

Simulation Analysis of Preheater Charge to the Rotary Furnace

Simulation Analysis of Preheater Charge to the Rotary Furnace

Diagnostics of sintering processes on the basis of PCA and two‐level neural network model

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