Evaluation of neural models applied to the estimation of tool wear in the grinding of advanced ceramics
作者：
Highlights：
• Tool condition monitoring in grinding of advanced ceramics using neural networks.
• Acoustic emission and power signals were used in several statistical parameters.
• Results showed that the ANN were highly successful in estimating tool wear.
• Errors was less than 4%.
• The models will help to improve product quality and increase productivity.
摘要
•Tool condition monitoring in grinding of advanced ceramics using neural networks.•Acoustic emission and power signals were used in several statistical parameters.•Results showed that the ANN were highly successful in estimating tool wear.•Errors was less than 4%.•The models will help to improve product quality and increase productivity.
论文关键词：Ceramic grinding,Intelligent systems,Neural networks,Advanced ceramics
论文评审过程：Available online 14 May 2015, Version of Record 31 May 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.05.008
