【摘要】 本文研究了采用多种传感信号经人工神经网络估计刀具磨损量的方法，提出了有监督线性特征映射算法，研究了网络参数对学习速度和网络精度的影响，并与多层前向网络（ＢＰ算法）进行对比。研究表明，有监督线性特征映射网络具有学习快、精度高的优点，具有广阔的应用前景更多还原

【Abstract】 In this paper, a Supervised Linear Feature Mapping (SLFM) is proposed to estimate tool wear. The influences of network parameters on learning speed and pelformance and the comparison with back-propagation algorithm (BP) are discussed. The results point that SLFM with the advantages of fast learning and high accuracy is a potential approach to estimate tool wear.更多还原