Surface Roughness Intelligent Prediction on Grinding

被引：0
|
作者：
Zhang, Dingtong [1 ]
Ding, Ning [2 ]
机构：
[1] Jilin Prov Agr Machine Res Inst, Changchun 130022, Peoples R China
[2] Changchun Univ, Coll Mech Engn, Changchun 130022, Peoples R China
来源：
PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON MATERIAL, MECHANICAL AND MANUFACTURING ENGINEERING | 2015年 / 27卷
关键词：
grinding; surface roughness; prediction; fuzzy neural network; AE;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Grinding is generally the final process, and it is closely related with the surface quality of the component. Now, it's difficult to measure the surface roughness until the grinding process is finished. The purpose of this research was to study the roughness prediction and avoid the defect happening in the grinding process. A surface roughness prediction model was built using the acoustic emission (AE) signal and Fuzzy-neural networks. Tests were performed, and the result verifies the feasibility of the proposed model.
引用
收藏
页码：2166 / 2169
页数：4
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