摘要
刀具作为DNC车间不可缺少的资源,其全寿命周期管理受到许多大型制造企业的重视,而刀具信息的标识和寿命预测是实现刀具管理的难点和关键。针对刀具信息标识,主要研究了刀具信息的直接标刻技术和刀具信息的自动识别技术,提出了用条状光源作为辅助光源的方法来提高条码识别率的方法;针对刀具寿命预测,提出了基于BP神经网络的预测方法,介绍了该算法的基本思想,并给出了实验结果。
Tool is indispensable resources of DNC workshop. Tool management based total life is affected by many large manufacturing enterprises attention. Tool marking and identification and life prediction are difficult and pivotal of tool management. According to the tool marking and identification, direct carving technology and automatic identification technology of tool were discussed, put forward strip light source as auxiliary illuminant method to improve the barcode recognition rate. According to the tool life predic- tion, a forecast method based On the BP neural network was proposed. The basic idea of the algorithm was introduced and experimental results were given.
出处
《组合机床与自动化加工技术》
北大核心
2013年第3期134-136,共3页
Modular Machine Tool & Automatic Manufacturing Technique
关键词
DNC
全寿命周期
刀具标识
寿命预测
DNC
total life
tool marking and identification
life prediction
作者简介
作者简介：殷锐（1975-），女，四川岳池人，西北工业大学明德学院讲师，硕士，主要从事计算机辅助设计研究，（E—mail）370761791@qq．com。
