The capacity of the rotor excavator depends largely on the operation of the subsystem for digging. There is a great contribution to the correct and sharp teeth when the capacity is the highest. In the function of time, the teeth become clogged due to abrasive wear, or changes in their geometric shape. To analyze the bucket wheel drive in depend on wear of the cutting elements in this study adaptive neuro fuzzy inference system (ANFIS) approach was implemented. ANFIS is a type of artificial neural network combined with fuzzy logic inference which is suitable for nonlinear data samples. The main goal of the study was to establish dependence on how the wear of cutting elements affects the operation of the bucket wheel drive. According to the results prediction of the horizontal frequency has the highest accuracy (R²= 0.7612, r = 0.8724, RMSE = 91.4881). Combining specific energy consumption and vibration on the input pair of the shaft would make a major step forward from existing scientific knowledge.

转子挖掘机的能力在很大程度上取决于挖掘子系统的操作。当容量最大时，对正确和锋利的牙齿有很大的贡献。在时间的函数中，牙齿由于磨料磨损或几何形状的变化而被堵塞。为了分析取决于切割元件磨损的铲斗轮驱动，本研究中采用了自适应神经模糊推理系统（ANFIS）方法。ANFIS是一种结合模糊逻辑推理的人工神经网络，适用于非线性数据样本。这项研究的主要目的是建立对切割元件的磨损如何影响铲斗轮驱动器操作的依赖性。根据结果​​预测，水平频率的精度最高（R ²= 0.7612，r = 0.8724，RMSE = 91.4881）。将特定的能量消耗和轴输入对上的振动相结合，将使现有的科学知识向前迈出一大步。