基于离散元的稻板田旋耕功耗预测模型研究
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

公益性行业(农业)科研专项(201503136)、国家重点研发计划项目(2017YFD0301303)和国家自然科学基金项目(51605182)


Prediction Model of Rotary Tillage Power Consumption in Paddy Stubble Field Based on Discrete Element Method
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    针对旋埋刀辊在对长江中下游稻板田耕作时存在的高功耗问题,基于离散元方法构建稻板田旋耕功耗预测模型,以辅助旋埋刀辊功耗检测。连续3年对稻板田土壤含水率的进行监测,发现土壤含水率与其塑限接近,说明稻板田土壤塑性较差,结合土壤受载后的形变及破坏特点,最终选定HertzMindlin with Bonding颗粒接触模型表征稻板田土壤的粘结和破坏情况。根据旋耕作业形式的特殊性和旋埋刀辊的结构特点,沿幅宽方向缩小旋埋刀辊的尺度,在旋耕测试平台的辅助下,完成标定参照试验。利用离散元软件建立旋耕作业模型,进行等步长爬坡试验,通过步阶次序建立接触参数与功耗指标之间的函数关系,代入标定参照试验功耗值,最终确定稻板田旋耕功耗预测模型的接触参数取值,完成模型的构建。为进一步验证该模型的适用性,在不同作业工况下对通用刀辊和旋埋刀辊进行误差对比试验,结果显示,预测误差范围为3.63%~9.48%,均值为6.65%,结合方差分析说明,稻板田旋耕功耗预测模型适用于不同旋耕刀辊及工况下的功耗预测。还原刀辊真实尺度的田间试验功耗预测误差范围为2.50%~12.81%,均值为7.28%,刀辊结构在缩放过程误差变化较小,说明模型能够准确反映旋埋刀辊在稻板田作业的功耗情况。

    Abstract:

    The rotary burying blade roller is suitable for soil cultivation and straw returning in paddy stubble field in the middle and lower reaches of the Yangtze River, but the power consumption is too high. Because of the complex interaction mechanism of the structure parameters of blade roller, the high cost of trial production, the short suitable cultivation period of farmland and the long test period cycle, it is impractical to optimize the design of the cutter roller simply by the field test method. Based on the discrete element method, a prediction model of rotary tillage power consumption the paddy stubble field was constructed to assist the detection of power consumption of the rotary burying blade roller. According to the monitoring of soil moisture content in the paddy stubble field for three consecutive years, it was found that the soil moisture content was close to its plastic limit, which indicated that the soil plasticity in the paddy stubble field was poor. Combined with the form of soil damage, HertzMindlin with Bonding particle contact model was selected to characterize the adhesion and damage of the soil in the paddy stubble field. In view of the particularity of rotary tillage operation and the structural characteristics of the rotary burying blade roller, the scale of the blade roller was reduced along the width direction, and the calibration reference test was completed with the help of rotary tillage test platform. In the discrete element software, the model of rotary tillage was established, and the functional relationship between contact parameters and power consumption index was established through the equal step climbing test. Combined with the power consumption value of calibration reference test, the contact parameter value of the rotary tillage power consumption prediction model in the paddy stubble field was finally determined, and the model was established. In order to further verify the applicability of the model, the error comparison test was carried out on the universal blade roller and the rotary burying blade roller under different working conditions. The results showed that the average prediction error was 6.65%, and the range was between 3.63% and 9.48%. Combined with variance analysis, the prediction model of rotary cultivation power consumption in paddy stubble field was suitable for the prediction of power consumption under different rotary cultivation blade roller and working conditions. The average error of power consumption prediction of the real scale field test of reduction roller was 7.28%, and the range was between 2.50% and 12.81%. In the process of scaling, the error of the roller structure was changed little, which showed that the model could be used in the field test.

    参考文献
    相似文献
    引证文献
引用本文

祝英豪,夏俊芳,曾荣,郑侃,杜俊,刘政源.基于离散元的稻板田旋耕功耗预测模型研究[J].农业机械学报,2020,51(10):42-50. ZHU Yinghao, XIA Junfang, ZENG Rong, ZHENG Kan, DU Jun, LIU Zhengyuan. Prediction Model of Rotary Tillage Power Consumption in Paddy Stubble Field Based on Discrete Element Method[J]. Transactions of the Chinese Society for Agricultural Machinery,2020,51(10):42-50.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2020-01-02
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2020-10-10
  • 出版日期: 2020-10-10