Cement Rotary Kiln Research Articles

Magnesium aluminate spinel nanoparticle influences upon the technological properties of MCZ composite brick for RCK lining

Fabrication of magnesia-calcium zirconate (MCZ) composite brick from Egyptian magnesite and zirconia (9.8 wt%) through adding different concentrations (2, 4, 6 wt%) of magnesium aluminate spinel rich magnesia (M-MA) nanoparticles as a modifier was experimented. Densification parameters, cold crushing strength (CCS), corrosion towards cement clinker components (CKC), and other technological properties of the produced bricks were investigated. The results revealed that MCZ brick containing 2.00 wt% of M-MA spinel gave the optimum mechanical properties, thus the strength was fortified by 44.8%. In addition, the penetration resistance and coating behavior toward the clinker components and the thermal shock cycles of the produced bricks were also enhanced with the addition of nano spinel. The investigated bricks showed higher technological properties compared with the refractory products offered in the market for the cement kiln. Accordingly, the brick free from spinel can be highly offered to transition and cooling zones of rotary cement kiln (RCK), while MCZ bricks containing spinel nanoparticles are recommended for lining the burning zone. Moreover, hazard chromite usage for improving coating adhesion can be superseded by environmental safe of nano-MA.

Calculation of the formation process of clinker inside the rotary cement kiln

This study examined the effect of the liquid phase on the heat required for clinker formation and the Coating index, and the relation of the Burning zone temp with the clinker and the heat required for clinker formation. The selection of the liquid phase at 1450 temperatures is being materials difficulty in the Burning, and 1338 is being materials easy in the Burning. All tests and tests were conducted at the Nile Cement Company. The results proved that the more difficult the materials are, the more the Heat required for clinker formation and increase the cost of cement production, and the Coating thickness is weak but strong. The materials easy Burning being little the Heat required for clinker formation and Decreases the cost of cement production, and the Excessive but unstable coating with tendency to form thick ring formation. The found average difference in Heat required for clinker formation between temperature 1338 °C and 1450 °C is 82.26 kJ/kg-clinker representing 2.23% of Total heat input are 3686 kJ/kg-clinker.

A Modified Moving Window dynamic PCA with Fuzzy Logic Filter and application to fault detection

Principal Component Analysis (PCA) model is constructed from measured data and used to monitor new testing samples. In fact, the statistical independency assumption between observations is true only for long sampling intervals. Nowadays, industrial systems are sophisticated and fast for which this assumption becomes no longer valid and the current observation becomes highly dependent on the past observations. In another hand, Dynamic PCA (DPCA) is a PCA extension to deal with the aforementioned problem, but monitoring process using this method with fixed control limits showed a high False Alarms Rate (FAR), high Missed Detection Rate (MDR) and long Detection Time Delay (DTD). In this paper, a Modified Moving Window DPCA (MMW-DPCA) with Fuzzy Logic Filter (FLF) is proposed to address the above issue. The developed monitoring scheme continually updates control limits throughout an obtained DPCA-based model. The adaptive thresholds are established by moving a fixed size window over the data. The dynamic behavior of the data is handled by DPCA, whereas the sensitivity enhancement and the FAR reduction are handled by the developed adaptive thresholds for which the FLF is employed to ensure robustness to outliers and noise without affecting the fault detection performances. The proposed technique has been tested on Tennessee Eastman Process (TEP). It has been compared to other well-known fault detection methods. The obtained results demonstrate that the MMW-DPCA with FLF detects different types of faults with high accuracy and in a short time delay. The experimental application of the MMW-DPCA with FLF has been carried out on cement rotary kiln. The obtained results illustrate that the proposed method has successfully detected a real fault.

Design of a Generalized Predictive Controller for Temperature Control in a Cement Rotary Kiln

In this paper a generalized predictive controller (GPC) for effective control of clinkerization temperature in a cement rotary kiln is designed. By using methods for identification of dynamic systems a mathematical model of the plant under study is obtained, whose validation results showed a high adequacy degree. The design of the GPC controller is performed based on the mathematical model obtained. It is shown that the designed controller allows controlling the plant under study with a high accuracy considering different real industrial operation scenarios. The comparative simulation results of the control system with PID and GPC controllers showed a better performance when the GPC controller is applied.

Improvement of an Adaptive Threshold Technique for Fault Detection in a Cement Rotary Kiln

In this paper, we suggest to use a two-dimensional plot characterizing the statistical variability of a large-sized multivariate data. This graphical representation is based on the mean and variance values. The two statistical parameters plot is used to assess fault detection performances in a cement rotary kiln system. The adaptive threshold technique is shown to result in more accurate and reliable detection. The threshold is established through several repeated experiments under the healthy mode with the same operating conditions. An adequate statistical test is used to examine the validity of the adaptive threshold estimation approach. At each mean’s subinterval for all experiments, a confidence interval closely linked to the distribution frequencies of the variance as a random variable is obtained. In addition, several significance levels are considered to show the performances of the proposed adaptive thresholding technique compared to the limitations of the fixed threshold through the rate of false alarms. Two different experimental faults are considered to demonstrate the effectiveness and accuracy of the adaptive threshold in terms of no false alarms and negligibly small missed alarms in comparison to the fixed threshold technique.

Fabrication of MgO-CaZrO3 refractory composites from Egyptian dolomite as a clinker to rotary cement kiln lining

Dolomite is used as basic lining for rotary cement kiln due its high refractoriness, corrosion resistance against basic environments and high coating performance, but its poor hydration resistance limits its use. In this work, Egyptian dolomite was converted into outstanding refractory magnesia-calcium zirconate composite (M-CZ) by the addition of 37.8–47.8 wt% zirconia. The mixtures were milled, uni-axially formed and fired at a temperature of 1400–1550 °C for 2 h. Thermal analysis, phase composition, microstructure, densification parameters, and other technological properties of the fired specimens were investigated. It was found that sintered M-CZ composite with bulk density (3.95 g/cm3), cold crushing strength (170 MPa), and high coating ability can be obtained by firing Egyptian dolomite with 37.8 wt% zirconia at temperature 1500 °C with the formation of belite as a secondary product. This composite can be nominated to be produced on a large industrial scale.

Single-step prediction method of burning zone temperature based on real-time wavelet filtering and KELM

The single-step prediction of burning zone temperature plays an important role in the safety and stability control of cement rotary kiln. This is because, the abnormal temperature events can be found as early as possible and the operator can take effective emergency measures in time. In this paper, the burning zone temperature single-step prediction method based on real-time wavelet filtering and kernel extreme learning machine is studied. Firstly, the visual inspection device is used to detect the burning zone temperature. And then, the amplitude limited filtering method is used to weaken the effects of temperature anomalies. On this basis, the real-time filtering of the burning zone temperature is realized by combining the sliding time window and wavelet filtering method. After that, the single-step prediction of burning zone temperature is realized by combining the sliding time window and kernel extreme learning machine method. At last, the burning zone temperature prediction method is validated. The minimum root mean squared error of the 5 consecutive days is 0.4259°C. The single average running time of model training and prediction of kernel extreme learning machine is much less than support vector regression, which is very helpful for the online prediction of burning zone temperature. The result shows that the burning zone temperature single-step prediction method proposed in this paper is feasible and effective.

A Study on the Failure of Steel Chains in Rotary Cement Kilns

The failure of steel chains which are used in rotary cement kilns costs cement companies a significant price. This study investigated the causes of chains failure at the Kufa cement plant and proposes new materials that can serve for a prolonged period of time. Two grades of steel chains were investigated including DIN 1.4742 (AISI 10F) and St37. Ten samples of chains from different locations from the kiln flame have been taken after 30 days and after 180 days of continuous work inside the rotary cement kiln. To study the effect of the distance from the kiln flame on the DIN 1.4742 (AISI 10F), another two samples have been replaced the St37 grade at a distance of 28.2 m. Chemical analysis for each sample under study has been carried out in order to highlight the differences between the used chain and the original chain in terms of alloying elements weight. An optical images of the unused and used chains of DIN 1.4742 (AISI 10F) steel grade have been taken to understand that the change occurs in the grain size. SEM-EDS technique was also applied to understand the possible segregation of elements. The results showed that the decrease of alloying elements pct, especially Cr, in the microstructure was the main reason of chain failure by corrosion/erosion mechanism. Preventing Cr from segregation can prolong the life of kiln chains during service. The study suggests new steel grades to replace DIN 1.4742 (AISI 10F) and St37 steel grades.

Effect of the calcium alumino-titanate particle size on the microstructure and properties of bauxite-SiC composite refractories

Alkali resistance and thermo-mechanical properties of the transition zone of cement rotary kilns refractories are the key factors affecting their service life. Calcium alumino-titanate (CAT) containing bauxite-SiC composites were prepared using bauxite, SiC, CAT, Guang Xi white clay, α-alumina, and metallic silicon powder as starting materials and Al(H2PO4)3 as the binder. The effects of the CAT particle size on the phase composition, microstructure, thermo-mechanical properties, and alkali resistance of the CAT-containing bauxite-SiC composites during firing were investigated. The results reveal that the CAT particle size strongly affects the composites’ microstructure and sintering densification. With decreasing particle size, the particle-particle and particle-matrix interfacial bonding deteriorates gradually. When CAT particles are added, the specimens show higher strength, refractoriness under load, and residual rupture strength than the specimens with fine CAT powders. Specimens with fine CAT powders show lower coefficient of thermal expansion compared to the specimens with CAT aggregates. The alkali attack test confirms that the bauxite-SiC composite refractories with CAT aggregates show better alkali resistance than those with CAT fine powder. According to the alkali mechanism, 1) K vapors penetrate the specimen through the open and connected pores and cracks, 2) K vapors react with anorthite and corundum to form kalsilite accompanied by the formation of a liquid phase and new cracks.

The effects of in situ formation of Y3Al5O12 on property improvement of magnesium aluminate spinel refractories

Magnesium aluminate spinel is widely used in cement rotary kilns, in the iron and steel industries, as well as in glass melting furnaces due to its excellent performance and chemical stability at both room temperature and elevated temperatures. In spite of these advantages, there are some practical problems during production of magnesium aluminate spinel refractories due to their poor sinterability: poor mechanical properties and poor creep resistance. These issues can cause problems during service. This study improved the sinterability of spinel refractories and in turn improved mechanical properties while decreasing the creep rate. This was done by forming a second low creep rate phase of yttrium aluminum garnet in the matrix structure. The addition of Y2O3 and reactive Al2O3 accelerated the densification process and increased the cold strength. There was a significant increase in the hot modulus of rupture due to the formation of YAG or the solid solution with spinel.

Kalman Filter based Fault Detection and Replacement Signal Generation of Sensor Measurements in Cement Rotary Kiln

Kalman Filter based Fault Detection and Replacement Signal Generation of Sensor Measurements in Cement Rotary Kiln

Evolution of Refractory Materials for Rotary Cement Kiln Sintering Zone

Development of refractory materials for the high-temperature zone of the rotary kilns used in the cement industry that is the second-largest user of refractory materials is given in the article. It is shown that the history of refractory materials used in this rotary kiln high-temperature zone commenced with alumina-silicate materials and ended with specially developed periclase-based materials used currently. Advantages and drawbacks of these materials are considered. Basic information is provided about the manufacture of cement for consideration of possible chemical reactions between cement kiln raw material and refractory material components.

M-CZ composites from Egyptian magnesite as a clinker to RCK refractory lining

Processing of magnesia-calcium zirconate (M-CZ) composites as clinker for manufacturing refractory bricks of rotary cement kilns (RCK) were produced from Egyptian magnesite and zirconia. 4.8–24.8wt% of zirconia was added as a modifier to Egyptian magnesite. The mixtures were milled, uni-axially formed and fired at 1550°C for 2h. Phase composition, microstructure, physical, mechanical thermal properties and wettability by Portland cement clinker of the obtained specimens were investigated. Addition of 9.8wt% zirconia to Egyptian magnesite gave the highest densification, best homogenous microstructure and the maximum cold crushing strength (174.9MPa). In addition, no free CaO was recorded. This composite can be strongly nominated for lining the RCK.

Function Block for Rotary Kiln Coating Disintegration Detection

Condition monitoring is an important field that can boost manufacturing processes to produce high quality and more quantities. This work presents the design of new Programmable Logic Controller (PLC) Function Block (FB) dedicated to the instantaneous detection of any coating piece disintegration from the wall coating formed by the processed material sticking naturally on the inner side of the cement rotary kiln. The detection is based on the on-line analysis of the kiln spinning electrical motor’s signal. The FB makes use of differences between the adjacent signal’s measurements values and logic functions to hide false alarms for the user whenever they break out due to kiln velocity set point abrupt changes. In steady state process operation, the technique provides highly reliable and accurate detection. Its application can be extended to any similar instantaneous abrupt changes occurring in other manufacturing processes.

Thermal Efficiency Evaluation of Souk Elkhamis Cement Rotary Kiln

Due to the fact that the cement industry is one of the discouraging energy-intensive industries, especially the thermal ones, study areas and aspects of the use of such a large amount of energy is one of the most important priorities in this area. This paper aims to highlight the merits and methods of use of this energy and calculate the output distribution of the energy produced from the burning of fuel to determine the amounts of wasted and used from them by conducting the thermal balance of the process in the kiln. It created that only about 47% of the energy is exploited in the completion of processes and chemical reactions, and the remaining approximately 53% is considered wasted. Part of this thermal energy lost is instrumental in some other purposes necessary in this industry as processes of drying and calcining of raw material nutrients before they entering the kiln, and stimulate the burning process of fuel in the kiln, etc., and the other, which is estimated at about 8.6% lose through the outer surface of the kiln to the surrounding. It was found that the total thermal energy entering the kiln to produce one kilogram of clinker equivalent 3658.53 kJ\kg when the kiln worked in about 89% of its production capacity, at the time that the amount of specific thermal energy used and registered when the initial tests carried out at the beginning of operating, which was equal to 3367.64 kJ\kg when the kiln worked with a capacity above 100%. This refers to the increase of approximately 9% of the energy. This paper recommends research into the causes of this increase of amount of heat consumption. It also recommends focusing on the study of the possibility to recovering this wasted energy, which found equal to 313.27 kJ\kg which is not an insignificant amount that can be neglected or ignored.

Designing and Implementation of Stable Sinusoidal Rough-Neural Identifier.

A rough neuron is defined as a pair of conventional neurons that are called the upper and lower bound neurons. In this paper, the sinusoidal rough-neural networks (SR-NNs) are used to identify the discrete dynamic nonlinear systems (DDNSs) with or without noise in series-parallel configuration. In the identification of periodic nonlinear systems, sinusoidal activation functions provide more efficient neural networks than the sigmoidal activation functions. Based on the Lyapunov stability theory, an online learning algorithm is developed to train the SR-NNs. The asymptotically convergence of the identification error to zero and the boundedness of parameters as well as predictions are proved. SR-NNs are used to identify some DDNSs and the cement rotary kiln (CRK). CRK is a complex nonlinear system in the cement factory, which produces the cement clinker. The experiments show that the SR-NNs in the identification of nonlinear systems have better performances than multilayer perceptrons (MLPs), sinusoidal neural networks, and rough MLPs, particularly in the presence of noise.

Numerical Study on the Influence of Operational Settings on Refuse Derived Fuel Co-firing in Cement Rotary Kilns

Cement production in rotary kilns requires large amounts of thermal energy, which is provided by combustion of different fuels. Substitution of fossil fuels by refuse derived fuels (RDF) can minimize production costs and reduce CO2 emissions, but often causes displacement of the sintering zone, impacts flame stability and cement quality. The current paper briefly introduces our numerical approach which describes particle motion and combustion characteristics of typical non-spherical RDF particles. By using these models in CFD simulations, a case study is presented. Fuel properties, primary- and secondary air settings and fuel feed location for a generic rotary kiln of industrial scale are varied to show the effects of operational settings on co-firing of RDF. Shift of flame shape and location as well as particle burnout are analyzed. Based on the information generated, optimized operational settings are identified and discussed.

Correlation between chemical composition and alkali attack resistance of bauxite-SiC refractories in cement rotary kiln

Abstract Alkali vapor release during alternative fuel combustion severely attacked bauxite-SiC refractories in cement rotary kiln. The present work investigated the effect of chemical compositions on microstructure, refractoriness under load and alkali attack resistance of bauxite-SiC refractories by the incorporation of different amount of micron sized α-Al 2 O 3 and microsilica powders. Results showed that the addition of α-Al 2 O 3 improved the refractoriness under load of specimens, whereas alkali attack products, e.g. KAlSiO 4 and KAlSi 2 O 6 phases were largely formed in the alumina-rich matrix, leading to the large volume expansion and cracks formation. By comparison, the addition of microsilica resulted in the decrease of refractoriness under load. Moreover, the volume expansion during alkali exposure can be controlled by increasing amounts of microsilica, which was attributed to the fact that less K-aluminosilicate phases mentioned above and more liquid were formed. In this case, the newly formed liquid blocked up some pores and further prevented the penetration of K vapor into the matrix. Alkali attack resistance and refractoriness under load of bauxite-SiC refractories can be balanced when the mole fraction of Al 2 O 3 was approximately 0.6 in the matrix of refractories.

Life cycle assessment of the use of alternative fuels in cement kilns: A case study

The benefits of using alternative fuels (AFs) in the cement industry include reduction of the use of non-renewable fossil fuels and lower emissions of greenhouse gases, since fossil fuels are replaced with materials that would otherwise be degraded or incinerated with corresponding emissions and final residues. Furthermore, the use of alternative fuels maximizes the recovery of energy. Seven different scenaria were developed for the production of 1 ton of clinker in a rotary cement kiln. Each of these scenaria includes the use of alternative fuels such as RDF (Refuse derived fuel), TDF (Tire derived fuel) and BS (Biological sludge) or a mixture of them, in partial replacement of conventional fuels such as coal and pet coke. The purpose of this study is to evaluate the environmental impacts of the use of alternative fuels in relation to conventional fuels in the kiln operation. The Life Cycle Assessment (LCA) methodology is used to quantify the potential environmental impacts in each scenario. The interpretation of the results provides the conclusion that the most environmentally friendly prospect is the scenario based on RDF while the less preferable scenario is the scenario based on BS.

Fault detection and diagnosis in a cement rotary kiln using PCA with EWMA-based adaptive threshold monitoring scheme

This paper presents main results of fault detection and diagnosis in a cement manufacturing plant using a new monitoring scheme. The scheme is based on multivariate statistical analysis and an adaptive threshold strategy. The process is statistically modeled using Principle Component Analysis (PCA). Instead of the conventional fixed control limits, adaptive thresholds are used to evaluate the common T2 and Q statistics as faults indicators. The adaptive thresholds are computed and updated using a modified Exponentially Weighted Moving Average (EWMA) chart. These techniques are merged together to construct a novel monitoring scheme whose effectiveness is demonstrated using involuntary real fault of a cement plant process and some simulated faulty cases.