车削过程切削力的计算机数值仿真

COMPUTERIZED NUMERICAL SIMULATION OF CUTTING FORCE IN TURNING PROCESS

切削力是表征切削过程最重要特征的物理量,其动态变化将直接影响加工过程中刀具与工件的相对位移、刀具磨损和表面加工质量等,所以对切削力建模是进行加工过程物理仿真研究的基础。因此在基于实时工况的切削实验研究基础上,考虑切削参数的因素,利用BP(back propagation)神经网络建立车削过程中的切削力的仿真模型。通过大量的样本训练,使神经网络能够对切削力进行较准确地数值仿真。

Cutting force is a basic parameter and it directly influences relative displacement between tool and workpiece, tool wear and surface quality in turning operation. Therefore, simulation model of cutting force is an important part of machining physical simulation research. A reliable and sensitive technique for monitoring the machining process without interrupting the process, is crucial in realization of research platform of simulation model. The prediction model based on back propagation neural network is established. After the training process is finished, the neural network becomes a knowledge-based system and accurately estimates them. Results showed that cutting force can be accurately estimated by using neural network in unknown cutting conditions.