Collaborative optimization of linear vibrating screen screening efficiency and dynamic response stability based on coupled DEM-MBK simulation

Xia, Xuhui; Gou, Lingxiao; Zhang, Zelin; Wang, Lei; Guo, Yuyao; Jing, Weiming

doi:10.1016/j.partic.2022.09.008

Cited by 10 publications

(4 citation statements)

References 30 publications

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“…It provided a basis for the performance improvement of the vibrating sieve. Xia et al [40] optimized the configuration of linear sieving process parameters based on the co-optimization method. The parameter combination scheme can increase the sieving efficiency by 3.28%.…”

Section: Fluentmentioning

confidence: 99%

Design and Motion Process of Air-Sieve Castor Cleaning Device Based on Discrete Element Method

et al. 2023

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In order to improve the cleaning effect of the castor shelling mixture, an air-sieve castor cleaning device was developed. The structure of the cleaning device was optimized by experiment and simulation based on the discrete element method. The results show that the sieving efficiency of the square distribution is 98.23% and the loss rate is 2.39%, both of which are better than the triangular distribution. The sieving efficiency in the condition of a 14 mm sieve hole diameter is 98.23%. For the conditions of 15 mm and 16 mm sieve hole diameters, the sieving efficiencies are 96.64% and 96.69%, respectively. Therefore, a sieve hole diameter of 14 mm is more beneficial for the sieving of castor capsules. The sieving efficiency is 94.0–99.5%, and the loss rate is 0.5–3.0% under 5°–9° sieve inclination. The cleaning effect is better through comprehensive analysis when the sieve surface inclination is 8°. The parameters of maximum sieving efficiency combination, minimum loss rate combination, and optimal cleaning effect were obtained by optimizing the operating parameters of the cleaning device. The operating parameters were adjusted, and then the three combinations of parameters were tested. It is found that the impurity content of castor seeds is within 1%, which meets the requirements of the device design. This study can provide a reference for developing high-efficiency castor cleaning devices.

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Section: Fluentmentioning

confidence: 99%

Design and Motion Process of Air-Sieve Castor Cleaning Device Based on Discrete Element Method

et al. 2023

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“…Peng [12] applied similar methods, showing improvement in mechanical properties compared to traditional methods when considering bending and random vibration. Xia [13] improved linear screening parameters through virtual experiments and dual-objective co-optimization, resulting in increased screening efficiency and improved dynamic response stability. Simulation based on finite element theory is considered the predominant approach for analyzing and optimizing the structural performance of vibrating screens [14].…”

Section: Introductionmentioning

confidence: 99%

Finite element analysis and optimization design of large vibrating screen based on equivalent static load method

Sun,

Sui,

Zheng

et al. 2024

Eng. Res. Express

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Vibrating screens have wide applications in various industries, ranging from agriculture to coal mining. In recent years, improvement in production have put forward higher requirements on the efficiency of vibrating screens. However, these large screens are prone to fatigue damage, particularly crack formation, over time. The emergence of substantial dynamic inertial forces can be attributed to the considerable body mass of a large vibrating screen. This study analyzed the structural strength of the HZXZ200x300 large vibrating screen, employing finite element simulation to identify the maximum equivalent stress and primary stress distribution. The main frame model of the vibrating screen box was constructed by integrating the equivalent static load and submodule methods. The model transitioned from dynamic response to static optimization under equivalent static and dynamic loads, significantly reducing calculation scale and enhancing optimization efficiency. Equivalent static sub-models were employed for topology optimization, determining the optimal structure for material performance distribution. This process yielded an optimal conceptual model for reconstructing the actual model. The structural strength was further improved by comparing three-dimensional and dynamic local stress relationships post-topological optimization, followed by reinforcing the vibrating screen structure and introducing reinforced bars for increased stability. The study showed that lightweight topology optimization significantly decreased the stress levels and improved the fatigue durability of beams. Local strengthening, accomplished via topology optimization, effectively reduced the maximum equivalent stress to 76.487 MPa, a decrease of 46.8%. The vibrating screen mass also decreased by 225 kg, a reduction of 14.9%. In summary, this study employed structural analysis, topology optimization, and local reinforcement to mitigate stress levels, enhance the fatigue life of a vibrating screen, and reduce its weight. This study offers an effective solution to the dynamic optimization challenges of complex structures.

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“…In addition to the external conditions such as the parameters of the screen machine, the shape characteristics of the material and the feed rate also have an important influence on the screening effect. Xia X et al [11] verified the importance of material shape characteristics for screening simulation by studying variable factors such as feed rate and screen aperture, and conducting simulation analysis with spherical shape and simulated particle shape.…”

Section: Introductionmentioning

confidence: 99%

Parameterization of Multi-Angle Shaker Based on PSO-BP Neural Network

et al. 2023

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It was possible to conduct a study on the shape and parameterization of the vibrating screen so as to explore the relationship between detailed vibrating screen motion parameters and particle group distribution under different screen surface states. The motion characteristics of particle groups in various scenes were investigated, screening performance of vibrating screen with complex parameters was studied, interaction between motion parameters of screen surface and motion of material groups in multi-component mixed particle groups was analyzed, segregation distribution law of multi-component mixed material groups was revealed, and this study presents simulation findings based on the discrete element program EDEM. The ensemble learning approach was used to examine the optimized model screen. It was revealed that the screen’s amplitude, vibration frequency, vibration direction angle, swing frequency, swing angle, and change rate of screen surface inclination all had a major impact on its performance. As a result, the vibrating screen’s running state was described by various parameter combinations, and the trend changes of several factors that affected the performance of the screen were examined. The investigation revealed that the particle swarm optimization backpropagation (PSO-BP) neural network model outperformed the backpropagation (BP) neural network model alone in terms of prediction. It had lower root mean square error (RMSE), mean square relative error (MSRE), mean absolute error (MAE), and mean absolute relative error (MARE) than the BP neural network model, but a larger R2. This model’s greatest absolute error was 0.0772, and its maximum relative error was 0.0241. The regression coefficient R value of 0.9859, which displayed the model’s strong performance and high prediction accuracy, showed that the PSO-BP model was feasible and helpful for parameter optimization design of vibrating screens.

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Collaborative optimization of linear vibrating screen screening efficiency and dynamic response stability based on coupled DEM-MBK simulation

Cited by 10 publications

References 30 publications

Design and Motion Process of Air-Sieve Castor Cleaning Device Based on Discrete Element Method

Design and Motion Process of Air-Sieve Castor Cleaning Device Based on Discrete Element Method

Finite element analysis and optimization design of large vibrating screen based on equivalent static load method

Parameterization of Multi-Angle Shaker Based on PSO-BP Neural Network

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