2000, Volume 2, Issue 12
Strategic Study of CAE >> 2000, Volume 2, Issue 12
Research on On-line Detecting Method and Key Technologies for Part Quality (Dimension and Surface Roughness)
School of Mechanical Engineering and Automation , Beijing Institute of Technology, Beijing 100081, China
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Abstract
To research on on-line detecting method and key technologies for part quality, based on the analysis of methods and features of on-line detecting of part dimension and surface roughness, an artificial neural network system for on-line detecting of part dimension and a fuzzy neural network system for on-line detecting of part surface roughness are developed. The Scheme of on-line detecting method for part quality can detect part dimension and surface roughness correctly.
Keywords
on-line detecting ; neural network ; fuzzy neural network ; dimension precision ; surface roughness
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References
[ 1 ] 陈爱弟 , 王信义 加工过程中尺寸在线检测技术[J].制造业自动化 , 2 0 0 0 , (10 ) :35～ 39 link1
[ 2 ] 陈爱弟 .零件加工质量实时在线检测技术研究[D].北京 :北京理工大学 , 2 0 0 0
[ 3 ] 陈爱弟 , 王信义 , 杨大勇 , 等 基于模糊聚类的刀具磨损量监测方法的研究 [J].北京理工大学学报 , 2 0 0 0 , 2 0 (3) :2 70～ 2 76 link1
[ 4 ] 王信义 , 计志孝 , 张建民 , 等 机械制造工艺学[M].北京 :北京理工大学出版社 , 1990 link1
[ 5 ] 焦李成 神经网络系统理论 [M].西安 :西安电子科技大学 , 1992
[ 6 ] 邢济收 刀具状态实时在线检测传感方式和检测方法研究 [D].北京 :北京理工大学 , 1997
[ 7 ] 王士同 神经模糊系统及其应用 [M ].北京 :北京航空航天大学出版社 , 1997
[ 8 ] 陈爱弟 , 王信义 .用于检测刀具磨损的声发射 (AE) 特征优选方法 [J].北京理工大学学报 , 2 0 0 0 , 2 0 (3) :2 76～ 2 80
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