基于ANFIS模糊神经网络的微钻头破损监测

Micro-drill Breakage Monitoring Based on ANFIS Fuzzy Neural Networks

使用轴向力和扭矩信号监测微孔钻削过程,提出了基于ANFIS模糊神经网络作为微钻头破损状态监测模型。该模型能够较准确描述钻头破损和信号特征之间的非线性关系,和常用的BP神经网络相比,具有收敛速度快和局部学习能力等优点。实验结果表明:采用ANFIS模糊神经网络对提高微钻头监测的准确性非常有效。

Micro-role drilling process was monitored in thrust and torque signals, and ANFIS fuzzy neural networks were constructed, which describe the nonlinear relationship between signal feature and micro-drill breakage, and have the advantages of fast convergence rate and local learning ability comparing with BP neural networks, experiments validate that the rate of checking out micro-drills breakage is very high by using ANFIS fuzzy neural networks, and the system has practical value very well.