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基于离散元法的切振共作深松机作业性能仿真分析及试验

Simulation analysis and test of the operation performance of shear vibration co-operation subsoiler based on discrete element method

  • 摘要: 针对深松装备应用于西南丘陵紫色土时存在作业阻力大、松土质量差、功耗高的问题,该研究提出切振共作深松方式并设计了一种切振共作深松机。运用离散元软件对非振动深松机和切振共作深松机在相同参数下进行仿真。仿真结果显示,切振共作方式能够有效减少深松机的耕作阻力。通过单因素试验得到切振共作深松机的最佳作业速度区间为0.9~1.1 m/s,最佳振动频率区间为9~15 Hz;通过正交试验得出深松作业最佳参数为:作业速度0.96 m/s、耕作深度300.24 mm、振动频率11.43 Hz。为了测试切振共作深松机的实际减阻性能,结合仿真结果并参考深松作业最佳参数,设置拖拉机前进速度1.0 m/s,作业深度为300 mm,振动频率为9、12和15 Hz,进行田间试验。结果表明:在相同速度和耕深条件下,切振共作深松机相较于非振动深松机均有明显的减阻效果,耕作阻力降低15.43%~37.56%;功耗降低8.87%~32.32 %,在振动频率为12 Hz时,减阻效果最佳,耕作阻力降低37.56%,功耗降低32.32%,土壤坚实度降低74.11%,土壤扰动系数为56.32%,深松深度为309 mm,深松深度稳定性系数为98.16%,深松深度及其稳定性符合行业标准。切振共作深松机减阻降耗效果明显,可为振动深松机的优化设计提供参考。

     

    Abstract: Deep-pine operation is often required for the high-power tractor for traction at present, leading to low operating efficiency. More importantly, the total power consumption of vibratory deep-pine operation is ever-increasing with the increase of vibration frequency. Therefore, there is an urgent need to carry out research on the high-efficiency vibratory deep-pine machine for high operational efficiency and low energy loss. In this study, a deep loosening machine was designed to cooperate with the cutting and local vibration. The loosening mode was adopted for the cutting first and vibration second, i.e. the front deep loosening shovel was fixed to break the soil. The angle of entry was always in the position of the lowest soil resistance. The rear shovel was vibrated around the shaft to loosen the soil. The soil resistance was reduced to increase the range of loosening for less crushing of soil, in order to effectively reduce the consumption of vibration energy. The discrete element method (DEM) was used to analyze the effect of cut-and-vibrate deep loosening on soil disturbance. Hertz Mindlin with Bonding model in EDEM was used to establish the contact model among soil particles. The cut-and-vibrate and traditional deep loosening were simulated to compare at the same time. The experimental model of the deep-pine shovel was established using SolidWorks2022 software and then saved in a format suitable for EDEM. The model was also imported into EDEM for constraining, driving, and simulation. The motion state of the simulation model was divided into two strokes of breaking and vibratory deep loosening, according to the actual vibratory during deep loosening. The cut-and-vibrate co-operative mode effectively reduced the tillage resistance of the deep-pine machine; The one-factor test showed that the optimal intervals operating speed and vibration frequency were 0.9-1.1 m/s, and 9-15 Hz, respectively; The orthogonal test demonstrated that the optimal parameters were obtained for the deep-pine operation: operating speed 0.96 m/s, tillage depth 300.24 mm, and vibration frequency 11.43 Hz. The actual performance of drag reduction was tested on the cut-and-vibrate deep-threader. The simulation was also combined with the best operating parameters of deep-threading. The field tests were conducted, where the forward speed of the tractor was set at 1.0 m/s, the operating depth was 300 mm, and the vibration frequency was set at 9, 12, and 15 Hz. The field test showed that the cut-and-vibrate deep pine machine shared the outstanding drag reduction under the same speed and plowing depth, compared with the non-vibrating deep pine machine. The plowing resistance was reduced by 15.43%-37.56%; The power consumption was reduced by 8.87%-32.32%. The drag reduction was the most significant when the vibration frequency was 12 Hz. The plowing resistance was reduced by 37.56%, the power consumption was reduced by 32.32%, the solidity of the soil was reduced by 74.11%, and the soil disturbance coefficient was 56.32%, and the deep pine depth of 309 mm, deep pine was reduced by 15 Hz. The stability coefficient for the deep pine depth of 309 mm was 98.16%. The deep pine depth and its stability were in line with the industry standard. The cutting and vibration co-production deep pine machine shared outstanding performance to reduce the resistance and consumption. The finding can provide a new reference to optimize the vibration deep pine machine.

     

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