航空发动机导管CNC弯曲回弹智能预测及补偿系统开发与应用

王睿乾; 潘林; 童志远; 张建国; 涂泉; 刘伟

doi:10.16080/j.issn1671-833x.2024.01/02.106

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航空发动机导管CNC弯曲回弹智能预测及补偿系统开发与应用

研究论文 | 更新时间：2025-10-30

- 航空发动机导管CNC弯曲回弹智能预测及补偿系统开发与应用
- 航空制造技术 2024年67卷第1/2期
- 作者机构：
  
  1. 哈尔滨工业大学,哈尔滨,150001
  2. 中国航发贵州黎阳航空动力有限公司,贵阳,550014
- 作者简介：
- 基金信息：
- DOI：10.16080/j.issn1671-833x.2024.01/02.106
  中图分类号：
- 纸质出版：2024
- 稿件说明：
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王睿乾，潘林，童志远，张建国，涂泉，刘伟. 航空发动机导管CNC弯曲回弹智能预测及补偿系统开发与应用[J]. 航空制造技术, 2024, 67(1/2): 106-111. WANG Ruiqian, PAN Lin, TONG Zhiyuan, ZHANG Jianguo, TU Quan,LIU Wei. Development and Application of Intelligent Prediction and Compensation System for Springback of Aero-Engine Pipes During CNC Bending[J]. Aeronautical Manufacturing Technology, 2024, 67(1/2): 106-111.

WANG Ruiqian, PAN Lin, TONG Zhiyuan, et al. Development and Application of Intelligent Prediction and Compensation System for Springback of Aero-Engine Pipes During CNC Bending[J]. Aeronautical Manufacturing Technology, 2024, 67(1/2).
王睿乾，潘林，童志远，张建国，涂泉，刘伟. 航空发动机导管CNC弯曲回弹智能预测及补偿系统开发与应用[J]. 航空制造技术, 2024, 67(1/2): 106-111. WANG Ruiqian, PAN Lin, TONG Zhiyuan, ZHANG Jianguo, TU Quan,LIU Wei. Development and Application of Intelligent Prediction and Compensation System for Springback of Aero-Engine Pipes During CNC Bending[J]. Aeronautical Manufacturing Technology, 2024, 67(1/2): 106-111. DOI： 10.16080/j.issn1671-833x.2024.01/02.106.

WANG Ruiqian, PAN Lin, TONG Zhiyuan, et al. Development and Application of Intelligent Prediction and Compensation System for Springback of Aero-Engine Pipes During CNC Bending[J]. Aeronautical Manufacturing Technology, 2024, 67(1/2). DOI： 10.16080/j.issn1671-833x.2024.01/02.106.

摘要

针对航空发动机导管数控（Computer numerical control，CNC）弯曲成形时回弹控制难度大、成形精度差的问题，开展了0Cr18Ni9和1Cr18Ni9Ti两种不锈钢导管的CNC弯曲工艺试验，获得了涵盖不同管径、壁厚、相对弯曲半径和弯曲角度的回弹数据。通过机器学习和遗传算法建立了导管CNC弯曲回弹预测模型，经遗传算法优化后，模型预测误差分布区间由[– 0.741°，0.771°] 缩小至[– 0.310°，0.314°]。在此基础上开发了导管CNC弯曲回弹智能预测及补偿系统，并用于典型的全尺寸航空发动机导管CNC弯曲工艺参数补偿和回弹控制。经检测，该系统补偿后的全尺寸航空发动机导管最大角度偏差为0.358°，完全满足实际生产精度要求，显著提高了航空发动机导管CNC弯曲精度和生产效率。

Abstract

Aiming at the problems of difficult springback control and poor forming accuracy during the CNC bending of aero-engine pipes

the CNC bending process experiments of 0Cr18Ni9 and 1Cr18Ni9Ti stainless steel pipes were carried out. The springback data of different pipe diameters

wall thicknesses

relative bending radius and bending angles were obtained. A springback prediction model of pipes during CNC bending was established through machine learning and genetic algorithm. After genetic algorithm optimization

the prediction error distribution of the model was reduced from [–0.741°

0.771°] to [–0.310°

0.314°]. On this basis

an intelligent prediction and compensation system for springback of pipes during bending was developed. It was used for the compensation on process parameters and springback control of typical full-size aero-engine pipes during CNC bending. After testing

it was found that the maximum angular deviation of the full-size aero-engine pipes compensated by the system was 0.358°

which fully met the actual production accuracy requirements

and significantly improved the CNC bending accuracy and production efficiency of the aero-engine pipes.

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