离散元法 (DEM) 参数是粒子系统运动建模的基础。为了验证微米级花粉颗粒DEM模拟参数标定的实用性，选取球形微米级番茄花粉作为研究对象进行参数标定实验。通过实验测量获得花粉形态、直径、密度等构成参数。然后，利用原子力显微镜测量和分析花粉的接触和碰撞过程，并利用Johnson-Kendal-Roberts（JKR）接触模型计算花粉的杨氏模量、表面能和恢复系数。设计Plackett-Burman试验，利用DEM模拟试验确定塑料地板花粉粒杨氏模量、花粉-花粉静摩擦系数、花粉-聚丙烯静摩擦系数的显着影响因素。使用最陡爬坡测试缩小了参数范围。根据Box-Behnken响应面分析的结果确定回归方程。求解该方程，花粉粒杨氏模量为5.25×10 6 Pa，花粉-花粉静摩擦系数为0.466，花粉-聚丙烯塑料静摩擦系数为0.417。从累积验证实验来看，测量与模拟的相对误差为1.01%，表明微米级花粉颗粒参数标定实验是可行的。此外，这里获得的参数可用于计算和预测花粉授粉过程。

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Discrete element method (DEM) parameters are the basis for modelling the motion of particle systems. To verify the practicality of calibrating DEM simulation parameters for micrometre-sized pollen particles, spherical micrometre-sized tomato pollen was selected as the research object for a parameter calibration experiment. Constitutive parameters such as the pollen morphology, diameter, and density were obtained through experimental measurements. Then, the contact and collision process of pollen was measured and analysed using an atomic force microscope, and Young's modulus, surface energy, and recovery coefficient of pollen were calculated using the Johnson-Kendal-Roberts (JKR) contact model. A Plackett-Burman test was designed, and the significant factors were determined using the DEM simulation test for Young's modulus of pollen grains, pollen-pollen static friction coefficient, and the pollen-polypropylene static friction coefficient for the plastic floor. The parameter range was reduced using the steepest climbing test. A regression equation was determined according to the results of the Box-Behnken response surface analysis. When this equation was solved, Young's modulus of pollen grains was 5.25 × 106 Pa, the pollen-pollen static friction coefficient was 0.466, and the pollen-polypropylene plastic static friction coefficient was 0.417. From the accumulation verification experiment the relative error between measurement and the simulation was 1.01%, which indicates that a calibration experiment of micrometre-sized pollen particle parameters is feasible. Furthermore, the parameters obtained here can be used to calculate and predict the pollen pollination process.