|
|||||
|
|
| 基于小波-神经网络纹理图像识别的刀具状态监测 | |
| 引用本文： | 杨晓波,冯冀宁,刘鸿运. 基于小波-神经网络纹理图像识别的刀具状态监测[J]. 组合机床与自动化加工技术, 2007, 0(12): 46-49 |
| 作者姓名： | 杨晓波 冯冀宁 刘鸿运 |
| 作者单位： | 1. 石家庄职业技术学院,机电系,石家庄,050081 2. 北京理工大学,电子工程系,北京,100081;河北师范大学,电子系,石家庄,050031 3. 河北师范大学,电子系,石家庄,050031 |
| 基金项目： | 河北省科技厅科技攻关项目 |
| 摘 要： | 介绍了一种采集旋转工件图像的光学监测系统,提出通过二维小波分析工件纹理图像,提取纹理特征,设计了基于动态和静态神经网络的刀具状态识别系统,该系统可用于自动化加工中刀具诊断,仿真证明了有效性。 |
| 关 键 词： | 刀具状态监测 图像处理 纹理分析 神经网络 |
| 文章编号： | 1001-2265（2007）12-0046-04 |
| 收稿时间： | 2007-07-16 |
| 修稿时间： | 2007-07-16 |
Tool Condition Monitoring Based on Texture Image Recognizing of Wavelet-neural Network |
|
| YANG Xiao-bo,FENG Ji-ning,LIU Hong-yun. Tool Condition Monitoring Based on Texture Image Recognizing of Wavelet-neural Network[J]. Modular Machine Tool & Automatic Manufacturing Technique, 2007, 0(12): 46-49 | |
| Authors: | YANG Xiao-bo FENG Ji-ning LIU Hong-yun |
| Abstract: | A Optical monitoring system for collecting the shape of turning workpice is introduced here,through 2-D wavelet analysis work piece image,extract texture feature,a tool conditions recognition system based on static and dynamic neural network is devised,the system can be used in cutting tool diagnosis in automatic precise processing,the validity of the theoretical algorithm is demonstrated by simulation results. |
| Keywords: | tool conditions monitoring image processing texture analysis neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |