Search Results (3)

The flip-flow vibrating screen (FFVS) is a novel multi-body screening equipment that utilizes vibrations to classify bulk materials in the field of screening machinery. The relative amplitude of FFVSs determines the tension and ejection intensity of elastic flip-flow screen panels, which is a critical operating parameter affecting the screening performance. However, FFVSs generally suffer from large variations of relative amplitude caused by the loading of materials and the changes in shear spring stiffness (the temperature changes of the shear springs lead to their stiffness changes), which significantly reduce the screening efficiency and lifespan of FFVSs. To address this problem, this paper proposes a nonlinear stiffness-based method for stabilizing the vibration amplitude of FFVSs using piecewise linear springs. By introducing these springs between the two frames, the sensitivity of the relative amplitude to shear spring stiffness is reduced, thereby achieving the stabilization of the relative amplitude of FFVSs. In this study, the variations of the vibration amplitude of the FFVS due to the loading of materials and the changes in shear spring stiffness were first demonstrated in a reasonable operating frequency range. Then the reasonable operating frequency range and dynamics of the resultant nonlinear flip-flow vibrating screen (NFFVS) with piecewise linear springs were investigated using the harmonic balance method (HBM) and the Runge–Kutta numerical method. The operating frequency region for the NFFVS lies between the critical frequency ${\omega }_{cs}$ and the frequency ${\omega }_{lb}$ corresponding to the saddle-node bifurcation point. Finally, a test rig was designed to validate the theoretical predictions. Theoretical and experimental results demonstrate that piecewise linear springs can effectively stabilize the relative amplitude of the FFVS. Full article

At present, spring tea yield is mainly estimated through a manual sampling survey. Obtaining yield information is time consuming and laborious for the whole spring tea industry, especially at the regional scale. Remote sensing yield estimation is a popular method used in large-scale grain crop fields, and few studies on the estimation of spring tea yield from remote sensing data have been reported. This is a similar spectrum of fresh tea yield components to that of the tea tree canopy. In this study, two types of unmanned aerial vehicle (UAV) hyperspectral images from the unpicked and picked Anji white tea tree canopies are collected, and research on the estimation of the spring tea fresh yield is performed using the differences identified in the single and combined chlorophyll spectral indices (CSIs) or leaf area spectral indices (LASIs) while also considering the changes in the green coverage of the tea tree canopy by way of a linear or piecewise linear function. The results are as follows: (1) in the linear model with a single index variable (LMSV), the accuracy of spring tea fresh yield models based on the selected CSIs was better than that based on the selected LASIs as a whole, in which the model based on the curvature index (CUR) was the best with regard to the accuracy metrics; (2) compared to the LMSVs, the accuracy performance of the piecewise linear model with the same index variables (PLMSVs) was obviously improved, with an encouraging root mean square error (RMSE) and validation determination coefficient (VR²); and (3) in the piecewise model with the combined index variables (PLMCVs), its evaluation metrics are also improved, in which the best performance of them was the CUR&CUR model with a RMSE (124.602 g) and VR² (0.625). It showed that the use of PLMSVs or PLMCVs for fresh tea yield estimation could reduce the vegetation index saturation of the tea tree canopy. These results show that the spectral difference discovered through hyperspectral remote sensing can provide the potential capability of estimating the fresh yield of spring tea on a large scale. Full article

The transmission in automobiles is the core component to ensure operational stability. Heat accumulation in the meshing process will reduce the transmission efficiency and affect the service life. Here, the essential physical process to improve transmission heat dissipation is the dynamic evolution process and the thermal transfer characteristics of lubricating oil fields during gear meshing. This paper presents a modeling and solving method for gear meshing lubrication and thermal transfer features based on the volume of the fluid model and piecewise linear interface construction (VOF-PLIC). The dynamic mesh technique combines spring smoothing and reconstruction to optimize the numerical solution process. The dynamic evolution law of gear meshing lubrication and thermal transfer is obtained by analyzing the lubrication evolution process under different speed/steering conditions. The results show that the proposed modeling and solving method could well reveal the lubrication and thermal transfer laws of the gear meshing. The temperature of the gear meshing regions was higher than that in the other regions, and the lubrication temperature showed an increasing linear trend with the stirring process. As the gear speed increased, the meshing resistance moment increased, the transmission power loss increased, and the lubrication oil temperature was larger than that of the gearbox. The power loss under the clockwise rotation of the driving gear G4 was higher than that under the counterclockwise rotation of the driving gear. The relevant results can provide theoretical references for the dynamic analysis of automotive transmission lubrication and technical support for gear profile design and lubrication optimization. Full article