[1]张莹[],刘敏[],张定华[],等. 基于在线检测的叶片加工余量自适应优化方法[J].计算机技术与发展,2014,24(11):226-229.
　ZHANG Ying[],LIU Min[],ZHANG Ding-hua[],et al. An Adaptive Approach for Machining Allowance Balancing for Blade Based on Online Measurement[J].,2014,24(11):226-229.
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 基于在线检测的叶片加工余量自适应优化方法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
24
期数:
2014年11期
页码:
226-229
栏目:
应用开发研究
出版日期:
2014-11-10

文章信息/Info

Title:
 An Adaptive Approach for Machining Allowance Balancing for Blade Based on Online Measurement
文章编号:
1673-629X（2014）11-0226-04
作者:
张莹[1] ; 刘敏[2] ; 张定华[1] ; 吴宝海[1]
 1.西北工业大学 现代设计与集成制造技术教育部重点实验室；2.中航工业西安航空发动机 集团 有限公司 科技发展部
Author(s):
 ZHANG Ying[1];  LIU Min[2];  ZHANG Ding-hua[1];  WU Bao-hai[1]
关键词:
 ; 叶片; 在线检测; 装夹定位; 余量优化; 约束条件
Keywords:
 ; blade ; online measurement; workpiece localization; allowance balancing; constraint condition
分类号:
TP391.7
文献标志码:
A
摘要:
 针对复合制造工艺背景下叶片毛坯形状复杂、余量分布不均的特点，提出基于加工中心在线检测的叶片装夹定位与余量优化方法。首先，根据叶片毛坯的工艺特性，建立了加工余量自适应优化的统一数学模型。然后，讨论了三类典型叶片包括无余量叶片、带余量叶片以及变形叶片组的定位与余量优化问题，并依次给出了适应不同约束条件的定位优化求解算法。最后，结合加工中心的在线检测方式，提出了叶片加工余量自适应优化的自动定位流程。算例分析结果表明，文中所提方法能够有效控制各种不同加工工艺制造的叶片毛坯的余量分布，使其自适应变化以满足实际工艺要求。
Abstract:
 Aiming at the complex shape and uneven distribution allowance of blade blank under the background of composite manufactur-ing process,an approach to workpiece localization and allowance balancing based on online measurement is proposed. Firstly,according to the technological characteristics of blade blank,an unified mathematical model for machining allowance balancing is constructed. Then, the localization and allowance balancing problems of single blade with no allowance,with allowance and distortion blade groups are dis-cussed and the corresponding solutions of localization transformation are also provided. Finally,with the online measurement of machining center,the implementation process for workpiece localization and allowance balancing of blade are given. Examples results show that the allowance distribution of different blade blank can be controlled effectively,which can satisfy the actual process requirement adaptively.

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更新日期/Last Update: 2015-04-14