目前，小型旋翼类飞行器旋翼主被动防除冰技术成熟度较低，在过冷云雾条件下发生结冰普遍只能依靠自身旋转进行脱冰。掌握脱冰规律及准确预测脱冰行为对在复杂气象条件下旋翼类飞行器设计及保障飞行安全至关重要。针对小型旋翼类飞行器飞行高度普遍较低的特点，开展明冰条件下旋翼脱冰试验及预测模型研究。探究不同转速、水含量(Lw)和云雾体积中值直径(D50)对脱冰时间和位置的影响规律。研究结果表明：脱冰时间随转速和Lw的增大而降低，脱冰位置随转速的增大而逐渐向桨尖移动，D50在20～40 μm之间变化则并未对脱冰行为产生明显影响。基于试验结果，提出了一种可快速预测脱冰时间和位置的经验模型。预测结果显示：在已知任意2组工况脱冰数据的基础上，可实现对未知工况脱冰情况的有效预测，其中脱冰时间平均预测准度达88.2%，脱冰位置平均预测准度为84.1%。针对试验中呈现的扇形和月牙形两种脱冰截面冰形，提出了一种基于无量纲冰厚的判定方法。利用此判定方法，对未知脱冰截面冰形工况进行预测，脱冰时间和位置平均预测准度分别为91.0%和88.4%。

At present, the active and passive anti-icing/deicing technology for small scale rotorcraft is low in maturity, and it can only rely on its own rotation for ice shedding when ice accumulates under the icing conditions. It is very important to master the ice shedding law and predict the shedding behavior accurately for the design and flight safety of rotorcraft under complex weather conditions. According to the characteristics of low flight height of small scale rotorcraft, the ice shedding test and prediction model of rotor under glaze ice condition are carried out. The effects of different rotational speed, liquid water content (L_w) and median volume diameter (D₅₀) on shedding time and location were investigated. The results show that the shedding time decreases with the increase of rotational speed and L_w, the shedding location gradually moves towards the rotor tip with the increase of rotational speed, and the change of D₅₀ between 20—40 μm has no significant effect on the shedding behavior. Based on the experimental results, an empirical model is proposed which can predict the shedding time and location quickly. The results show that, on the basis of the known shedding data of any two icing conditions, the shedding characteristics in other conditions can be effectively predicted, in which the average accuracy on shedding time is 88.2%, and the average accuracy on shedding location is 84.1%. In the model prediction, a judgment method based on dimensionless ice thickness is proposed for the two ice shapes of the ice shedding section presented in the test. Using this method, the conditions of unknown ice shedding section is predicted, and the average prediction accuracy of shedding time and location is 91.0% and 88.4%, respectively.