Vertical Roller Research Articles

Numerical Study of Flow Field and Particle Motion Characteristics on Raw Coal Vertical Roller Mill Circuits

In order to improve the motion characteristics of particles in vertical roller mills (VRMs), the assumption that different structures of helical guide blades affect the internal flow field of the VRMs was put forward. The distributions of fluid velocity and vorticity in VRMs were analyzed, and the mechanism affecting the motion of particles and the separation performance was studied. The study took the MMLM2550 (supplied by Jiangsu Dahuan Group, China; grinding table diameter of 2550 mm) VRM as the research object, whose structure was improved by adding helical guide blades. The results showed that, with the increase in the width of blade, the air flow trajectory and the distribution of vorticity improved, which was conducive to the transport of particles. However, changing the thickness of the blade had little effect on the internal physical field of the VRM and particle motion characteristics. Therefore, the influence of blade’s thickness on these factors was ignored. With the increase in the number of helical guide blade turns, the direction of the helical guide blade remained consistent with the trajectory of the movement of particles, making it more conducive to the discharge of particles from the VRM. The height of the helical guide blade had a great influence on the flow field and the particle motion characteristics. The smaller the blade height, the greater the reflux in the primary separation zone, and stronger the irregular circulatory motion of particles, thus increasing the movement time and the distance of particles. With the increase in the number of blades, the airflow speed increased in the flow channel, so that the particles moved with the airflow at high speed, while the movement time was effectively shortened. The study provides valuable guidance for the improvement of VRM structures, and serves as a reference for characterizing the motion of particles and enhancing the internal flow field in VRMs.

Multiphysics Simulation of a Vertical Roller Mill in Matlab®/Simulink®

The development of innovative products increasingly requires interdisciplinary collaboration among the fields of mechanical engineering, electrical/electronic engineering, and software. The growing complexity of products, driven by increased automation, poses significant challenges. Many equipment manufacturers optimise their development processes using software tools. By leveraging simulations and virtual models, product development time can be reduced. Additionally, the number of costly test bench experiments can be significantly minimised. Furthermore, numerical simulation is gaining importance in the field of predictive maintenance.To fully harness the potential of simulation, it is crucial to accumulate experience across various products and processes and validate them using real-world physical test benches. In this contribution, a vertical roller mill (VRM) is modelled across domains. Subsequently, selected simulation analyses are conducted and validated against measurement data from the physical demonstrator and analytical or empirical calculation models. Additionally, the suitability of the virtual prototype for model-based virtual commissioning is examined. The multi-physical model was developed using Matlab®/Simulink®, including the toolbox Simscape and Stateflow.

AUTOMATIC SOLAR PANEL CLEANING SYSTEM

The exponential growth of solar energy as a renewable energy source emphasizes the importance of optimizing solar panel efficiency and maintenance. One critical challenge for solar cells is the impact of environmental factors, particularly the accumulation of dust and debris on panel surfaces. To solve this problem, our project introduces an automatic cleaning system for solar panels. offers a dual function of user-scheduled cleaning and intelligent automatic cleaning. In addition, the system has a vertical roller brush mechanism that ensures precise and efficient cleaning.The user-scheduled cleaning mode provides a flexible interface that allows users to customize cleaning schedules according to individual preferences and usage needs.Intelligent automatic cleaning mode marks a paradigm shift in solar panel maintenance. Using advanced sensors such as light sensors and a real-time clock, the system calculates the capacity of the solar panels in real time. This data-driven approach intelligently schedules cleaning cycles, dynamically adapting to actual maintenance needs. Light sensors measure the intensity of sunlight, while a real-time clock ensures accuracy and adapts cleaning processes to environmental and seasonal changes. .Key Words: Solar panel, cleaning,Scheduling,Sensor operation,Automatic.

Fabrication and characterization of new Fe3O4@SiO2@TiO2-CPTS-HBAP (FST-CH) nanoparticles for photocatalytic degradation and adsorption removal of rhodamine B dye in the aquatic environment

In this study, Fe3O4@SiO2@TiO2-CPTS-HBAP (FST-CH) nanoparticle was prepared for the simultaneous adsorption and photocatalytic degradation of aromatic chemical pollutants (Rhodamine B dye) in aqueous solution. FST-CH nanoparticle was characterized using scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), Energy Dispersive X-Ray (EDX) Fluorescence Spectrometer and X-Ray Diffraction (XRD) spectroscopy. The photocatalytic activity of rhodamine B dye (RhB) was evaluated with a Kerman UV 8/18 vertical roller photoreactor. About 56% of RhB in aqueous medium was adsorbed by FST-CH nanoparticles with only 45 min of stirring in the dark, and about 77.01% was degraded or converted to other structures under the photoreactor for 120 min. The photocatalytic degradation of RhB (apparent rate constant: 0.0026 mg dm−3 min−1) occurred by a pseudo-second order reaction. In addition, the recovery of the prepared magnetic FST-CH nanoparticle by an external magnetic field, exhibiting good magnetic response and reusability, shows that the obtained magnetic FST-CH nanoparticle is stable and maintains high degradation ratio and catalyst recovery even after four cycles. Thus, the prepared FST-CH nanoparticle can be highly recommended for its use in potential applications of water decontamination.

Research on on-site installation process of grinding roller of SLM5600 Vertical roller mill

SLM5600 vertical roller mill is widely used in 6000t/d cement clinker production line, the main parts of SLM series mill is a whole disc and three grinding roller, the roller in addition to the regular change with the liner accident, also need to regularly check and change with the bearing and oil seal and the wear bushing, by SLM5600 roller mill Department of heavy cement plant machinery maintenance conditions are limited, many manufacturers can only be shipped back to my company roller for repair and replacement parts, resulting in long period of maintenance, repair costs, provide a set of field assembly roller assembly process in this paper, according to the process maintenance workers on-site replacement parts and grinding roller assembly.

Sound-based diagnosis of failure in a vertical roller mill

Sound-based diagnosis of failure in a vertical roller mill

Unsupervised feature selection using chronological fitting with Shapley Additive explanation (SHAP) for industrial time-series anomaly detection

With the development of the industrial Internet of Things (IIOT), an amount of industrial multivariate time series (IMTS) data has been collected by various sensors. IMTS data anomaly detection plays an important role in industrial process monitoring and operation condition identification. Many real-world IMTS datasets usually have a large number of redundant features, which may lead to deviation of the anomaly detection model and misunderstanding of potential feature correlation. Hence, it is essential to select features that have critical and effective effects on anomalies and operation conditions. In this paper, a feature selection that introduces knowledge-based target variables into inner feature selectors (IFSs) is proposed as a wrapper method, referred to as ILSFS. The IFS is constructed by integrating a timing fitter, which is established based on the long and short-term memory (LSTM) network, with the Shapley Additive explanation (SHAP) assisted to eliminate unimportant features. The experiments were conducted on two datasets: the vertical roller mill dataset (VMD) of a slag milling factory in Jiangsu Province and the public server machine dataset (SMD). Compared with None feature selection, SVM-RFE, LGBM -Boruta, Genetic-based methods, and other SHAP-assisted feature selection methods such as XGBSVFIR and ShapHT+, the experiment results highlighted the proposed methodology ILSFS improves the best F1 score of each the above baselines by 0.2799, 0.2208, 0.2647, 0.1882, 0.3775, 0.2765 for the VMD and 0.1475, 0.0586, 0.0567, 0.0638, 0.0519, 0.2250 for the SMD on the downstream anomaly detection. The best precision of the ILSFS for the VMD and the SMD was 0.8224 and 0.9499, respectively, while its best recall was 0.7353 and 0.4902, respectively.

Parameters for the Grinding Process in Vertical Mills Using Optimization Methods

Vertical roller mills, VRMs, are widely used for grinding raw materials in factories engaged in the extraction and processing of minerals. Any machine used for grinding or crushing consumes around 30 to 40% of the energy of a factory. The loading pressure, table rotation speed, moisture content, outlet temperature and pressure rollers are variables that can be controlled to decrease the specific energy consumption Ecs. This paper poses an optimization problem in order to reduce the energy consumption of a VRM used to produce cement and to find the optimal parameters of the operating variables. Several packages are used to solve the nonlinear programming problem, obtaining very concise results, but the results provided by the Pyomo package are used. Comparing the result of the objective function with the energy consumption of a well-known cement company in Ecuador, it is concluded that the optimized parameters are able to reduce by 25% the energy consumption guaranteeing a minimum production of 2200 tons of cement per day, so the model is correctly validated.

Influence of vertical shaft machine parameters on increasing productivity of the processed product

In this article, the influence of the force pulling the base plate of the vertical shaft machine up along the chain on the pair of compression shafts and the dependence of the moisture squeezed from the semi-finished product being processed on the diameter of the shafts are experimentally studied. The scientific novelty of the research is the development of an improved experimental design of a vertical type shaft machine that flattens the folded areas of wet semi-finished products and compresses excess moisture. The practical significance of the results of the research is explained by the development of an improved vertical type shaft machine for the mechanical processing of the semi-finished products with improved quality indicators of semi-finished products, energy saving, increasing productivity. In experimental studies, a regression equation was developed that determines the amount of excess liquid squeezed out of the semi-finished product during vertical transmission, depending on the diameter of the compression shafts, traction force and transmission speed. Based on the obtained results, graphs were constructed and analyzed. Currently, worldwide attention is being paid to improving the quality of leather products by using energy and resource-saving technologies. As can be seen from the above review, the quality of the processed material is influenced by many parameters of technological machines. Therefore, we believe that an experimental study of the parameters of a vertical roller machine on the properties of the processed leather semi-finished product is relevant.

Optimisation of the performance of a new vertical roller mill by computational fluid dynamics simulations

The performance of two new Vertical Roller Mills (VRM) has been analysed using Computational Fluid Dynamics (CFD). The results show notable air ingress from the bottom of the mill, due to moving components in the mill. This is detrimental to mill performance as the milled powder gets recirculated back into the milling region and reduces the overall milling efficiency. Optimisation of the mill design has been carried out based on CFD modelling results. Proposed reconfigurations produce a positive pressure upstream, suppressing air ingress. Design modifications were implemented in a pilot-scale mill, resolving the air ingress problem. Additionally, erosion patterns were computed for the mill geometry and qualitatively confirmed by visual inspection of the mill.

Operational Failure of Vertical Roller Attached to a Grinding Mill: Root Cause Analysis

Operational Failure of Vertical Roller Attached to a Grinding Mill: Root Cause Analysis

Impacts of Clinker Storages Heat Transfer, Its Effect on Vertical Roller Cement Performances: A Case Study of Cement Grinding Operations in Nigeria

Operational data indicates that vertical roller cement mills (VRCM) consumed lesser energy when compared to horizontal/ball mills. A case study of a vertical roller cement mills was carried out in Nigeria which was experiencing a lower production output and a higher energy consumption. This research was to investigate reasons behind the low production output on the VRCM. A thorough analysis was carried out on the clinker storage facilities and the heat transfer across the composite cylindrical clinker silo walls (off – spec and main clinker) both silos having the same design but with different dimensions and with different application purpose. The off-spec clinker silo has a design capacity of 1,800 tons and main clinker silo a design capacity of 60, 000 tons and both silo stores hot clinker that left the kiln clinker cooler at approximate temperature of 95oC. The analytical results shows that the rate of heat transfer across the main clinker composite walls was 728 kW and the rate of heat transfer across the off-spec clinker composite walls was 217.15 kW. Numerical simulation was also carried out using ANSYS simulation package and the results obtained were in good agreement with the results obtained theoretically. The ratio of heat loss on the main clinker composite walls to off-spec clinker composite walls was 3.35:1.

Fault Prognosis System on Face-Mask Body Machine with Adabelief-Backpropagation Neural Network

Ultrasonic welding workload on vertical roller welding components on face-mask body machine in making masks has a highvibration of up to 20kHz. This high vibration causes the locking bolt to loosen the serrations, thus causing a greater failure of function, such as wear and tear on the teeth. If this function fails, it will cause downtime and high costs in the waiting process for the cleat component to be remanufactured. The damage prognosis system based on the condition of this machine implements a Classification of types of damage along with recommendations for maintenance activities that need to be carried out on the Face-Mask Body Machine. Classification of the type of damage to this system using There is a Belief-Backpropagation Neural Network (BPNN), a method for looking for weight settings on a neural network based on the error rate obtained in the previous iteration. This method is optimized using AdaBelief, which can adapt the step size based on the "confidence" of the previous gradient to get Convergence rates and generalization abilities better so that these types of problems can be known from the vibration signal of the machine which previously the signal was parsed using wavelet packet decomposition into frequency bands to obtain component data with low or high frequency. From the results of system performance testing, the modeling accuracy is 98.4%, so this system can be declared good and feasible to use in slack detection of vertical roller welding cleat fixing bolts.

Comparative analysis of conventional and fuzzy FMECA approach for criticality analysis of a vertical roller mill

Comparative analysis of conventional and fuzzy FMECA approach for criticality analysis of a vertical roller mill

Prediction and Optimization of Wear Depth on Rectangular Tube Surface in Roll Forming

The outer surface of the tube is worn under the interaction between the velocity difference and rolling pressure, in the process of rolling the circular tube into a rectangular tube. In order to predict the wear depth, according to the characteristics of roll forming, the causes of wear in the forming process are analyzed. The finite element model of rolling forming was established based on Archard theory, and the 40 mm × 27.5 mm × 3 mm SUS304 stainless steel rectangular tube was simulated. The simulated results were compared with a test rolling of the steel tubes of the same size material, and the wear areas were found to be highly consistent, which verified the accuracy of the finite element model. The effects of the friction coefficient and the flat roller angular velocity on the simulation results which wear depth were analyzed, and the regression model of wear depth was established by response surface method. The results showed that the flat roller angular velocity had the greatest effect on wear depth; moreover, the flat roller friction coefficient was the second, and the vertical roller friction coefficient was the lowest. The minimum value of the regression model was optimized, the simulation value of the optimization scheme was compared with the optimized value, and the error of the two values was less than 5%, which verified the correctness of the regression model. The wear depth of the rectangular tube after optimization was reduced by 64.69% compared with that before optimization, which verified the effectiveness of the optimization results.

Efficient machine learning model to predict fineness, in a vertical raw meal of Morocco cement plant

Soft sensor enables computing parameters that can be physically impossible to measure. This work aims to develop a soft sensor for raw meal fineness in a vertical roller mill of a cement plant. In previous research, some key indicators of the process were ignored. It is well known that vertical raw meal is feeded with heterogenous material that impacts raw meal fineness, and therefore, can deteriorates prediction accuracy of the soft sensor. To deal with this constraint, one-year history of industrial data was exploited and processed by a robust multivariate outlier identification method, followed by process expert outlier verification. Then a particular attention was given to process and material quality parameters using a statistical method to test parameters significance on fineness based on data variance calculation. Eight process and four quality parameters were retained to develop robust nonlinear model using artificial neural network: Bayesian regularization and Levenberg Marquart, then compared with Support vector regression with different acquisition function and kernels to tune and select optimum model hyperparameters. The best model performance was obtained with the Bayesian regularization algorithm.

The evolution of cross-sectional dimension for double wall brazed tube in the multi-pass roll forming

The manufacturing process of double wall brazed tube (DWBT) consists of the multi-pass roll forming from the flat strip to double wall structure and brazing process. And the poor roundness of cross section for DWBT in the multi-pass roll forming not only affects the forming accuracy and quality, but also restricts the subsequent brazing process of DWBT. Thus, the parameters of Hill’48 yield criterion for the steel strip were firstly determined in this paper, and the reliable 3D finite element model of the multi-pass roll forming of DWBT was established based on ABAQUS/Explicit platform. Then the cross-sectional dimension of DWBT after each roll forming was analyzed. The results show that the multi-pass roll forming of DWBT requires the cooperation of the forming roller, horizontal roller and vertical roller, and the radius of the horizontal roller profile becomes larger with the increasing roll pass. The evolution of cross section is accompanied by the accumulation of equivalent strain, following the forming sequence of two arms on both sides, inner wall, outer wall and sizing process. An expression representing roundness is proposed, and it is concluded that the roundness of the outer tube is better than that of inner tube. Moreover, the cross-sectional distribution of the outer tube is more uniform along the circumferential direction.

Kinematic Characteristics of Vertical Runner and Numerical Simulation Analysis of Rock Breaking

In order to solve the problems of PDC teeth easy to collapse and fail in hard, hard and soft interlaced formations and gravel bearing formations, low mechanical speed, and difficult orientation caused by high torque response of pdc bits in directional drilling, this paper proposes a new type of composite bit with vertical wheels on the blade. Through theoretical analysis, the rotating conditions of the vertical wheel are obtained, that is, the contact angle of the cutting teeth of the vertical wheel must be greater than the center angle of its two adjacent teeth. At the same time, the cutting tracks generated by the previous vertical wheel unit experiments are analyzed, and the causes of different cutting tracks are obtained. Finally, the rock breaking of the PDC teeth under the pre damage of the vertical wheel is numerically simulated and analyzed, and it is concluded that the force on the PDC teeth is closely related to the relative height between the cutting teeth of the vertical wheel, It increases with the increase of relative height. When the relative height is 2mm, the tangential force on the PDC tooth is 4.78 times that when the relative height is 0mm, and the axial force is 2.47 times that when the relative height is 0mm. At the same time, the relationship between the force on the PDC teeth and the normal deflection angle and the rake angle of the vertical roller is not obvious.

Effect of Quartz in Clay on Grindability of Raw Mixes for Cement Production

High quartz content in clay substantially impacts the grinding of raw mix, quality of clinker and final cement produced. The presence of quartz requires very fine grinding and a long sintering time to react significantly, all of which are very expensive. This study assessed an extensive plant sample which involved a vertical roller mill to determine the correlation between quartz content in clay to the 90 μm residue, feed rate, clinker microstructure and mill power. The characterisation study performed on raw materials revealed three clay categories based on quartz content, namely low, normal and high quartz at (42.4%–48.8%), (57.1%–64.9%) and (81.5%–89.3%), respectively. The grinding test showed an increment of 90 μm residue for high-quartz clay. Meanwhile, high, medium and low feed rates generated the most coarse, coarse and fine products, respectively. Based on the distribution curve of mill products, high quartz content in clay significantly reduced the particles passing percentage. Coarser particles were observed to be present in mill products for the high-quartz category compared to the low-quartz clay and normal-quartz clay, signifying inadequate size reduction for the high-quartz clay in the vertical roller miller. The power consumption was higher (7.2 kWh/t–9.0 kWh/t) for grinding raw mixes that contained high-quartz clay than low-quartz clay. This study provided a significant relationship between grindability and the amount of quartz content in clay with the purpose of optimising the grinding process when dealing with high-quartz content in clay.

A cement Vertical Roller Mill modeling based on the number of breakages

This study investigated a mathematical model for an industrial-scale vertical roller mill(VRM) at the Ilam Cement Plant in Iran. The model was calibrated using the initial survey's data, and the breakage rates of clinker were then back-calculated. The modeling and validation results demonstrated that according to the bed-breakage mechanism in VRM, clinker particles only stay in the VRM for a short time. Particles in the VRM haven't a 1 to 3 times greater chance of breaking due to their brief time in the VRM. Matrix model's results model provides a more robust prediction based on the number of 2-times clinker breakage in VRMs (R2 = 0.9916, MSE = 5.3526, accuracy = 94.6474). Also shown by the results of the matrix modeling, the S increased with decreasing the particle size. In contrast, the population balance model increased with increased particle size.