摘要
In this paper, a Supervised Linear Feature Mapping(SLFM) algorithm, as a modification of the Kohonen Self Organizing Mapping (SOM),is proposed. The applications in cutting tool wear estimation and quality control and the comparison with a back propagation (BP) algorithm are discussed. The results show that the SLFM algorithm requires less training time and has higher accuracy compared with the BP algorithm. It might be a great potential approach to integrate multi sensor information in process control.
In this paper, a Supervised Linear Feature Mapping(SLFM) algorithm, as a modification of the Kohonen Self Organizing Mapping (SOM),is proposed. The applications in cutting tool wear estimation and quality control and the comparison with a back propagation (BP) algorithm are discussed. The results show that the SLFM algorithm requires less training time and has higher accuracy compared with the BP algorithm. It might be a great potential approach to integrate multi sensor information in process control.
