• CN：11-2187/TH
• ISSN：0577-6686

• 数字化设计与制造 •

### 柔性材料加工变形影响因素提取层次分析方法

1. 广东工业大学机电工程学院 广州 510006
• 出版日期:2016-06-05 发布日期:2016-06-05
• 作者简介:邓耀华,男,1978年出生,博士,副教授,硕士研究生导师,美国密西根大学“吴贤铭”制造研究中心博士后高级研究员。主要研究方向为机械加工过程检测与控制、智能制造。E-mail：dengyaohua@gdut.edu.cn;陈嘉源(通信作者),男,1991年出生,硕士研究生。主要研究方向为数据挖掘、人工智能。E-mail：chenjiayuan2014@163.com;刘夏丽,女,1992年出生,硕士研究生。主要研究方向为模式识别、智能控制。E-mail：lxlnzb@126.com
• 基金资助:
国家自然科学基金(51205069)、广东省科技计划(2014A010104012,2015B090901009)、2014年广东省联合培养研究生示范基地-佛山市南海区瀚天科技城研究生联合培养基地和佛山市科技创新团队(2015IT100102)资助项目

### Study of Deformation Factors Extracting on Flexible Material Machining by Analytical Hierarchy Process

DENG Yaohua, CHEN Jiayuan, LIU Xiali, ZHANG Qiaofen, CHEN Sicheng, WU Liming

1. School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006
• Online:2016-06-05 Published:2016-06-05

Abstract: Deformation factors reduction is the priority problem for the compensation control predictive modeling of flexible material machining, however, for the reasons of self-properties and machining characteristics of flexible material, it causes deformation factor increasing, and those factors are interrelated and overlapped simultaneously. Considering analytic hierarchy process which belongs to information decision field, has the advantage of calculating impact of various factors in decision system by using limited quantitative information. The analytic hierarchy process is introduced and to be used in the study of deformation factors extracting of flexible material machining, according to it, the machining deformation factors extraction model is constructed, the model includes target layer, criterion layer and index layer which correspond to deformation factor significance, machining properties and deformation factors. Computational formula between extraction attribute P of machining deformation factors is deduced, and take influence degree vector Wp as evaluating indicator to establish calculation programmer of extraction algorithm, finally, experiments are carried. Experimental tests show that the factor set extracted by analytic hierarchy process is similar to theses method of Pawlak and information entropy. The prediction error by hierarchical analysis process is 13.76% and 9.43%s decreased comparing to Pawlak and information entropy, which proved that the analytic hierarchy process can effectively and expediently extract the machining deformation factors set.