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切削加工表面粗糙度影响因素及预测建模综述
引用本文:陈光军,韩松鑫,潘佳琦,侯帅,孙光兴.切削加工表面粗糙度影响因素及预测建模综述[J].机床与液压,2020,48(13):185-188.
作者姓名:陈光军  韩松鑫  潘佳琦  侯帅  孙光兴
作者单位:天津职业技术师范大学机械工程学院,天津300222;佳木斯大学机械工程学院,黑龙江佳木斯154007;佳木斯大学机械工程学院,黑龙江佳木斯154007;天津宝涞精工集团股份有限公司,天津301800
基金项目:国家自然科学基金;基本科研业务费项目;黑龙江省自然科学基金
摘    要:表面粗糙度对零件的使用寿命有很大影响,正确、合理地选用表面粗糙度数值,可以减少零件的加工费用,提高零件的使用寿命。对表面粗糙度的评定参数及测量方法进行了介绍,重点阐述了表面粗糙度的产生机制和切削参数对表面粗糙度的影响;从回归分析法、响应曲面法和神经网络建模方法3个方面综述了表面粗糙度预测与建模的研究进展。指出用多参数表征表面粗糙度和建立加工表面粗糙度的预测、优化和工艺工况为一体的综合预测模型是未来发展方向。

关 键 词:表面粗糙度  加工表面  切削参数  预测  建模

Review on the Influence Factors and Predictive Modeling of Surface Roughness in Machining
CHEN Guangjun,HAN Songxin,PAN Jiaqi,HOU Shuai,SUN Guangxing.Review on the Influence Factors and Predictive Modeling of Surface Roughness in Machining[J].Machine Tool & Hydraulics,2020,48(13):185-188.
Authors:CHEN Guangjun  HAN Songxin  PAN Jiaqi  HOU Shuai  SUN Guangxing
Affiliation:(School of Mechanical Engineering, Tianjin University of Technology and Education, Tianjin 300222, China;School of Mechanical Engineering, Jiamusi University, Jiamusi Heilongjiang 154007, China;Tianjin Baolai Precision Machinery Industry Group Co., Ltd., Tianjin 301800, China)
Abstract:The surface roughness has a great influence on the service life of the parts.The correct and reasonable choice of surface roughness value can reduce the processing cost of the parts and improve the service life of parts.The evaluation parameters and measurement methods of surface roughness were introduced.The mechanism of surface roughness and the effect of cutting parameters on surface roughness were emphatically described.The advances in surface roughness prediction and modeling were reviewed from regression analysis,response surface method and neural network modeling.It was pointed out that the future development direction was to characterize the surface roughness with multiple parameters and to establish a comprehensive prediction model integrating the surface roughness prediction and optimization and process conditions.
Keywords:Surface roughness  Machined surface  Cutting parameter  Prediction  Modeling
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