关键词: 表面粗糙度监测, 贝叶斯网络, 传感器信号特征, 机器学习, 切削加工

Abstract: Aiming at the uncertainty of various factors on surface roughness,a surface roughness prediction model based on Bayesian network was proposed.The energy features of time domain and frequency domain were extracted directly from cutting force and workpiece vibration.The association relationship between surface roughness and sensor signal features were mined with Bayesian network learning process,and the monitoring result was obtained according to the probability distribution of roughness range.The effectiveness of proposed method was verified by the roughness experiment of milling process.

Key words: surface roughness monitoring, Bayesian network, sensory features, machine learning, cutting machining