|本期目录/Table of Contents|

[1]朱里红.大口径厚壁管中频弯制工艺参数多目标优化[J].工业仪表与自动化装置,2018,(05):43-46.[doi:1000-0682（2018）05-0000-00]
　ZHU Lihong.Multi-objective optimization of medium frequency induction heating process for large diameter pipe bending[J].Industrial Instrumentation & Automation,2018,(05):43-46.[doi:1000-0682（2018）05-0000-00]
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大口径厚壁管中频弯制工艺参数多目标优化

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2018年05期
页码:
43-46
栏目:
出版日期:
2018-10-15

文章信息/Info

Title:
Multi-objective optimization of medium frequency induction heating process for large diameter pipe bending
作者:
朱里红
成都理工大学 工程技术学院，四川 乐山 614000
Author(s):
ZHU Lihong
The Engineering &Technical College of Chengdu University of Technology,Sichuan Leshan 614000,China
关键词:
大口径管; 中频感应; 多目标优化; 数值模拟
Keywords:
large diameter pipe; medium frequency induction heating; multi-objective optimization; finite element simulation
分类号:
TG356.25
DOI:
1000-0682（2018）05-0000-00
文献标志码:
A
摘要:
大口径厚壁管中频感应局部加热弯曲工艺作为一种先进的加工方法已经被广泛地应用，然而在实际生产过程中仍存在着很多问题，故需要优化弯曲成形工艺参数。采用中心复合设计以椭圆度、减薄率和成形载荷为目标，建立相关工艺参数的响应面模型，得到对中频感应局部加热弯管成形质量影响较大的工艺参数为外壁温度、温度梯度、热变形区宽度和推制速度。优化结果显示，外壁温度t=1030~1070 ℃，推制速度v=0.3~0.4 mm/s时，成形质量最好。工艺试验证明采用多目标优化得到的工艺参数可以提高产品合格率。
Abstract:
Medium frequency induction heating for large diameter pipe bending is an advanced technique that has been widely used. However, the thickness control of outer wall and inner wall of pipe is still difficult in the actual production: outer wall tends to be thicker and inner wall tends to be thinner. Therefore,it is necessary to optimize the process parameters of bending.Combined central composite experimental design and a proper selection of design parameters sample,an accurate response surface model was built in order to decrease ovality, thickness reduction ratio and forming load. The response value of objective function was analyzed; and important influence factors for system stability were found, i.e heating temperature, heating width, temperature gradient and feeding velocity. The results indicate that the optimal value range were heating temperature of outer wall t=1030~1070 ℃, while feeding velocity v=0.3~0.4 mm/s. Practical results from multi-objective optimization can improve the product pass rate.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期：2018-04-12
基金项目：成都理工大学青年科学基金资助(C122016015)
作者简介：朱里红(1979)，男，四川仁寿人，副教授，硕士，研究方向为冶金节能技术和成形智能控制技术。
更新日期/Last Update: 2018-10-15