一种新的磨削加工砂轮锋利度在线建模与监测方法的研究

本文通过考察外圆磨削循环中工件每转实际磨削深度变化规律与砂轮锋利度的密切关系，提出用神经网络ＡＲＴ２模型对磨削过程中工件每转实际磨削深度变化规律进行数据处理，可以实现在线识别磨削过程砂轮的锋利度。针对磨削加工的特点，提出新的ＡＲＴ２模型匹配度判据。设计制作了相应的数据采集处理系统，对实际磨削过程不同工艺参数的情况下砂轮锋利度进行识别，证实了这种新的识别砂轮锋利度模型及监测系统是十分有效的。

Study on a New Method for Modelling and Monitoring Wheel Sharpness in Grinding

In this study, according to a careful observation of relation between wheel sharpness and change tendency of real grinding depth per revolution of workpiece in external grinding cycle, a new method is proposed by which wheel sharpness may be recognized on line in grinding process, with processing change tendency of real grinding depth per revolution of workpiece in grinding process by means of neural network ART2 model. In accordance with special features of grinding, a new matching degree formula of ART2 model is proposed. A corresponding system is also designed for collecting and processing data. Wheel sharpness is recognized on line under different groups of grinding process parameters. It has been proved that the new model and monitoring system is very effective.