摘要
刀具磨损监测过程是一个模式识别过程,模糊推理和人工神经网络都是进行模式识别非常有效的办法,针对模糊系统和神经网络各自表现出来的不足,将模糊推理和神经网络结合起来,充分利用模糊系统在处理结构性知识上的优势和神经网络在自学习和并行处理上的能力,形成模糊神经网络进行刀具磨损在线监测识别。通过研究模糊系统和神经网络的结合形势,选择模糊系统增强的神经网络进行识别计算,同时建立隶属函数对刀具磨损过程进行模糊划分,最后通过实验进行识别测试。
Tool wear monitoring process is a pattern recognition process, Fuzzy reasoning and neural networks are very effective to pattern recognition, because of shortcoming of fuzzy system and neural networks, this paper makes full use of fuzzy system which is advantage to deal with structure knowledge and neural networks that is good at self-learning and parallel processing to form fuzzy neural networks to monitor tool wear.By studying the situation of combination of fuzzy system and neural networks, this paper selects the neural networks enhanced by fuzzy system to recognise tool wear, and divide tool wear process by membership function at the same time, and finally recognise tool wear by experiment.
出处
《机械》
2011年第1期22-25,73,共5页
Machinery
