磨削条件的优化及表面粗糙度的预测与控制

中国机械工程 ›› 2011, Vol. 22 ›› Issue (2): 158-161.

磨削条件的优化及表面粗糙度的预测与控制

池龙珠

江苏技术师范学院，常州,213001

出版日期:2011-01-25 发布日期:2011-01-27
基金资助:
教育部留学回国人员科研启动基金资助项目(教外司留[2007]24号)
Scientific Research Starting Foundation for Returned Overseas Chinese Scholars （No. [2007]24）

Optimization of Grinding Conditions and Prediction and Control of Surface Roughness

Chi Longzhu

Jangshu Teachers University of Technology,Changzhou,Jiangsu,213001

Online:2011-01-25 Published:2011-01-27
Supported by:
Scientific Research Starting Foundation for Returned Overseas Chinese Scholars （No. [2007]24）

摘要/Abstract

摘要：

利用信噪比实验设计法和二次回归设计技术,对平面磨削中砂轮转速、工件速度、径向进给量及砂轮粒度等因素对表面粗糙度的影响规律进行了分析，各因素对表面粗糙度的影响由大到小依次为砂轮粒度、径向进给量、砂轮转速和工件速度。同时建立起表面粗糙度的回归预测模型，并以F检验法对其进行检验,回归预测模型的显著性水平为0.01，回归效果良好。



关键词:

信噪比实验设计法, 二次回归设计技术, 磨削加工条件, 表面粗糙度

Abstract:

Based on S/N-ratio experimental design and quadratic regression design technique, the effects of spindle speed, workpiece speed, depth of cut and grain size of wheel on the surface roughness of workpiece during plane grinding were investigated.It is found that the successive impact factors for the surface roughness are grain size, depth of cut, spindle speed and workpiece speed, respectively.An unary

linear regression model about the surface roughness was established and tested by F method. The test results show the significance level of the unary linear regression model is 0.01, which means a good regression effect.

Key words:

S/N-ratio experimental design, quadratic regression design technology, grinding condition;surface roughness

中图分类号:

TG580.12

池龙珠.

磨削条件的优化及表面粗糙度的预测与控制

[J]. 中国机械工程, 2011, 22(2): 158-161.

CHE Long-Zhu.

Optimization of Grinding Conditions and Prediction and Control of Surface Roughness

[J]. China Mechanical Engineering, 2011, 22(2): 158-161.

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