Mechanized onion planting is crucial for improving efficiency and reducing labor costs. However, traditional elliptical gear-driven planting mechanisms often exhibit issues such as unstable trajectories and excessively high velocities and accelerations. To address this, this paper proposes a parallelogram planting mechanism based on a denatured Pascal limacon gear drive. By analyzing the mechanism's operating principle and the transmission characteristics of the denatured Pascal limacon gear, a kinematic model was established. The effects of parameters such as gear denaturation coefficient, drive speed, and link dimensions on the planting point trajectory and motion velocity were investigated. Results indicate that the denaturation coefficient, crank length, and initial mounting angle significantly influence the mechanism's performance. Based on these findings, multi-objective optimization using a genetic algorithm was conducted to meet agronomic requirements. The optimized mechanism achieves a planting depth of 27 mm at a forward speed of 0.3 m/s and a gear angular velocity of 2 pi rad/s. Horizontal velocities at soil entry and exit approach zero, acceleration changes gradually during the planting phase, and operational stability is significantly enhanced. Compared to the elliptical gear drive configuration, it demonstrates superior overall performance.
To prolong the service life of the rolling bearings and improve the reliability of the associated mechanical systems, inspired by the leaves of Monstera deliciosa, eleven biomimetic texture patterns, featuring various leaf-geometry characteristics - such as leaf-veins, elliptical holes, and their combinations - were designed and prepared on the raceway of the shaft washer of cylindrical rollers thrust bearings using a laser surface texturing method. The effects of these leaf-inspired patterns on the tribological and friction-induced vibration performance of rolling bearings were systematically investigated under starved lubrication conditions. The results show that a significant "superposition effect" on vibration signals was observed in the earlier stages of testing, but this effect diminished over time. Larger aspect ratios of elliptical holes did not improve the friction-wear performance of the biomimetic textured groups. When the elliptic area was larger, the bearing experienced relatively lower wear losses, higher average coefficients of friction, and greater fluctuations in time-domain vibration signals. The influence of different elliptic areas on the frequency-domain vibration signals was minimal. This work would provide a valuable insight into the raceway optimization of rolling bearings.
Alumina ceramic gears exhibit excellent mechanical properties as well as resistance to high temperatures and corrosion, making them suitable for extreme working conditions that traditional metal gears cannot accommodate. However, their inherent high hardness and brittleness present significant challenges in ensuring high-quality surfaces during molding and manufacturing. In this study, alumina ceramic gears were polished using a picosecond pulsed laser. By proposing a novel alternating superimposed scanning strategy, processing errors were effectively reduced, and surface integrity was enhanced. A univariate experimental approach was used to optimize the key laser processing parameters, including laser power, scanning speed, number of scans, and line spacing. The optimal combination of parameters (7 W power, 220 mm/s scanning speed, 4 scans, and 0.005 mm line spacing) was finally determined to obtain a tooth surface with a surface roughness (S-a) of 1.091 mu m (+/- 0.025 mu m). Comparative analysis showed that the surface roughness was significantly reduced by 41.93 % to 44.53 % compared with the conventional machining (1.922 mu m). In addition, the microhardness of the laser-treated tooth surface increased by 6.36 % and showed improved resistance to tooth chipping under localized high-load conditions. The enhanced surface flatness and mechanical properties significantly improve the meshing performance required for mechanical transmission systems. Notably, the laser surface treatment method significantly reduces the processing cost compared with the traditional mechanical polishing process, providing a cost-effective alternative for ceramic gear molding surface treatment process. This paper innovatively applies laser polishing directly to the tooth surfaces of actual ceramic gears featuring complex curved surfaces, thereby providing crucial process support for their practical application in high-precision transmission systems.
This paper presents a novel double-arc geometric analytical model to analyze the static characteristics of convoluted air springs (CAS). The model assumes that the profile of the bellows is composed of double circular arcs with different radii of curvature and considers the effects of bellows stretching deformation. Based on this model, this paper proposes a hybrid analysis method that uses the CAS geometric analytical method instead of the computationally expensive fluid-structure interaction (FSI) static analysis. Using the geometric parameters and internal pressure of the CAS under loaded equilibrium, as derived from the proposed double-arc model, an FSI simulation model of the CAS is established in Fluent for subsequent static and dynamic characteristic analysis. The feasibility of the double-arc model and the proposed analysis method is validated through static and dynamic characteristic experiments of the CAS. Furthermore, the hybrid analysis method is applied to analyze the dynamic response of an air spring vibration isolation system. A comparison with the results of the traditional full-process FSI simulation demonstrates that the proposed method improves the average computation efficiency by approximately 10.8 % while maintaining computational accuracy.
This study investigates the deformation coordination of an engine crankshaft-bearing system and presents a tolerance-based method to improve stiffness matching. First, a continuous-beam analytical model is developed to derive bearing support reactions, with its accuracy being validated through a threedimensional finite element model under worst-case loading conditions. Then the Reynolds equation is combined with the Gumbel boundary condition to explain hydrodynamic effects. Based on the journal eccentricity, the load-carrying coefficient is described by fitting an exponential function. Finally, using the relative bearing clearance as the design variable, a clearance-optimization model is formulated to minimize the variance in support displacements. The results show that the sequential quadratic programming method after particle swarm optimization can improve the deformation coordination by 31 %. This method can provide a practical and computationally efficient guideline for improving structural stiffness matching and lubrication performance in crankshaft-bearing system design.
