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Identification, prediction and detection of the process fault in a cement rotary kiln by locally linear neuro-fuzzy technique
, Article 2009 International Conference on Computer and Electrical Engineering, ICCEE 2009, 28 December 2009 through 30 December 2009 ; Volume 1 , 2009 , Pages 174-178 ; 9780769539256 (ISBN) ; Fatehi, A ; Sharif University of Technology
Abstract
In this paper, we use nonlinear system identification method to predict and detect process fault of a cement rotary kiln. After selecting proper inputs and output, an input-output model is identified for the plant. To identify the various operation points in the kiln, Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained by LOLIMOT algorithm which is an incremental tree-structure algorithm. Then, by using this method, we obtained 3 distinct models for the normal and faulty situations in the kiln. One of the models is for normal condition of the kiln with 15 minutes prediction horizon. The other two models are for the two faulty situations in the kiln with 7 minutes...
Identification of nonlinear predictor and simulator models of a cement rotary kiln by Locally Linear Neuro-Fuzzy technique
, Article World Academy of Science, Engineering and Technology ; Volume 58 , 2009 , Pages 1121-1127 ; 2010376X (ISSN) ; Fatehi, A ; Sharif University of Technology
2009
Abstract
One of the most important parts of a cement factory is the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral movement of air and materials, together with chemical reactions take place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only in exceptional case; however, a large number of the involved parameters were crossed out and an approximation model was presented instead. This issue caused many problems for designing a cement rotary kiln controller. In this paper, we presented nonlinear predictor and simulator models for a real cement...
Simulation of Heat and Mass Balance in Rotary Kiln of Iron Pellets Induration
, M.Sc. Thesis Sharif University of Technology ; Yuzbashizadeh, Hossein (Supervisor)
Abstract
In this study, the heat and mass balance of rotary kiln of iron pellets induration was simulated. Due to large amount of heat transfer calculations, a quasi three-dimensional model has been used in this study. First, the freeboard heat condition was simulated via fluent program and the average temperature of freeboard was stablished. Then, a one-dimensional heat transfer model was developed using heat transfer equations. In this model, the heat transfer via conduction, convection and radiation in different parts of the kiln was included. Also, the bed reactions and their effect on bed temperature were evaluated. Finally, transversal movement and velocity of particles was studied. Transversal...
Identification of nonlinear predictor and simulator models of a cement rotary kiln by locally linear neuro-fuzzy technique
, Article 2009 International Conference on Computer and Electrical Engineering, ICCEE 2009, 28 December 2009 through 30 December 2009, Dubai ; Volume 1 , 2009 , Pages 168-173 ; 9780769539256 (ISBN) ; Fatehi, A ; Sharif University of Technology
Abstract
One of the most important parts of a cement factory is the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral movement of air and materials, together with chemical reactions take place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only in exceptional case; however, a large number of the involved parameters were crossed out and an approximation model was presented instead. This issue caused many problems for designing a cement rotary kiln controller. In this paper, we presented nonlinear predictor and simulator models for a real cement...
Identification and Abnormal Condition Detection of a Cement Rotary Kiln
, M.Sc. Thesis Sharif University of Technology ; Fatehi, Alireza (Supervisor)
Abstract
One of the most important parts of a cement factory is the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral movement of air and materials, together with chemical reactions take place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only in exceptional case; however, a large number of the involved parameters were crossed out and an approximation model was presented instead. This issue caused many problems for designing a cement rotary kiln controller. In this thesis, we employed a nonlinear system identification method for identification,...
Experimental Study of Drying and Calcination of Simulated High-Level Waste (HLW)
, M.Sc. Thesis Sharif University of Technology ; Samadfam, Mohammad (Supervisor) ; Zahakifar, Fazel (Supervisor) ; Zaheri, Parisa (Co-Supervisor)
Abstract
One of the novel methods of stabilization of nuclear waste is the use of vitrification technology. In order to stabilize high level wastes (HLLW) in glass, it is required that the elements are in their oxide form. Therefore, it is necessary to evaporate the waste and turn it into a solid form so that the elements can be converted into oxide form in the calcination furnace. Hence, one of the challenges of stabilization is the optimization of evaporation and calcination conditions. In this research, the parameters affecting evaporation were first investigated. Using laboratory measurements of application: temperature (110 to 180 °C), presence of nitric acid (0.5 to 4 mol/L), ratio of zirconium...
Identification, prediction and detection of the process fault in a cement rotary kiln by Locally Linear Neuro-Fuzzy technique
, Article World Academy of Science, Engineering and Technology ; Volume 58 , 2009 , Pages 1128-1134 ; 2010376X (ISSN) ; Fatehi, A ; Sharif University of Technology
2009
Abstract
In this paper, we use nonlinear system identification method to predict and detect process fault of a cement rotary kiln. After selecting proper inputs and output, an input-output model is identified for the plant. To identify the various operation points in the kiln, Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained by LOLIMOT algorithm which is an incremental tree-structure algorithm. Then, by using this method, we obtained 3 distinct models for the normal and faulty situations in the kiln. One of the models is for normal condition of the kiln with 15 minutes prediction horizon. The other two models are for the two faulty situations in the kiln with 7 minutes...