考虑自然风的气辅式喷雾雾滴飘失特性建模与补偿

气流辅助喷雾在雾滴减飘方面确有效果，然而大田作业时，其减飘效果受到自然风、喷雾流量、风筒出口风速、喷雾角等多种工况的严重影响。该文采用多相流计算流体动力学软件，建立三维流场几何模型，依据不同工况参数对雾滴漂移特性的影响，利用均匀设计安排试验方案，研究雾滴在自然风、辅助气流综合作用下在连续相和雾滴粒子离散相的耦合规律，通过流体动力学仿真完成训练样本采集，采用多元相关向量机回归方法建立不同自然风速下减飘模型，并通过模糊决策支持系统对作物茂密程度和喷嘴与冠层间垂直距离进行控制参数修正。试验结果表明：多元相关向量机回归模型预测飘失率的平均绝对百分比误差为2.56%，自然风扰动中实测和预测飘失率平均误差为8.92%，其飘失规律与所建飘失模型基本吻合。研究结果可为面向雾滴沉积效果的喷雾主动控制系统设计提供参考。

Modeling and compensation for characteristic of droplet drift on air-assisted boom spraying accounting for wind speeds

Abstract: Air-assisted boom spraying has proven to have a positive effect on drift reduction. However, its effects with certain operational parameters of air-assisted boom sprayers are varied depending on natural wind speeds, outlet velocities of air curtain, spraying flow, spraying angle and etc, thus the spray drift rate and deposition rate are not stable in the field working. For example, if wind speed is low, and airflow and outlet speed of wind duct are high, which not only increases the power consumption of the fan, but also directly blew the droplets to ground and formed serious spray loss. On the contrary, when the wind speed is high, the speed of air-assisted flow is not enough to overcome the influence of wind, the spray droplets is drifted. To provide the control parameters to achieve precise control model with pesticide effect, this paper, leveraged by a three-dimensional multiphase flow computational fluid dynamics (CFD) model with the consideration of wind speeds, inlet speed of air curtain, spraying flow and spraying angle, simulates the coupling interaction of natural wind (continuous phase), the air curtain (continuous phase) and the droplets (discrete phase) of the air-assisted boom sprayer to study the droplet drift characteristics. The uniform experimental design took into the four factors with five levels of L2- deviation of the uniform design table U25 being applied to arrange the simulation scheme. Two criteria, the drift rate and the downward velocity under the duct 0.5m, were used to evaluate the spraying performance under the computing utilizing CFD simulation results. The simulation results were collected as training samples, and the multivariate relevance vector machine (MRVM) regression method was utilized to establish the 4-inputs-2-outputs spraying drift model accounting for the varying natural wind. The CFD simulation and the MRVM model only considered the four factors which influenced the spraying effect, however the vertical distance when the dense degree, crop of nozzle and the crop canopy were not at the same time, influence of spray effect was also affected by these parameters. Therefore, a fuzzy inference system model considersing crop canopy dense degree and vertical distance between nozzles and canopy was established to correct the 3 control parameters. According to the experiment, spray system analysis and expert experience, 11 fuzzy rules with Gauss membership function were set up. By using the fuzzy logic toolbox, fuzzy inference system was defined to obtain the mapping between input and output. In order to quantitative analysis the modeling quality of the droplet drift characteristics, the 3MQ - 600 type air-assisted boom sprayer was used in the droplet drift test. Model tests showed that the mean absolute percentage error of the drift rate was 2.56%, and the spraying drift test of air-assisted boom sprayer prototype with natural wind disturbance had validated that the measured and predicted drift loss rate average error of 8.92%, which still showed the same interaction rule with the built spraying drift predictive model. This study provided the active control system with spraying ant-drift and droplet deposition effects-oriented control and decision-making model.