• CN:11-2187/TH
  • ISSN:0577-6686

›› 2000, Vol. 36 ›› Issue (12): 89-94.

• 论文 • 上一篇    下一篇

激光冲击强化效果的控制及人工神经网络预报研究

於自岚;曾丹勇;杨继昌;张永康   

  1. 江苏理工大学机械工程学院
  • 发布日期:2000-12-15

INVESTIGATION ON CONTROL OF EFFECT OF LASER SHOCK-PROCESSING AND PREDICTION BY USING ARTIFICIAL NEURAL NETWORK

Yu Zilan;Zeng Danyong;Yang Jichang;Zhang Yongkang   

  1. Jiangsu University of Science and Technology
  • Published:2000-12-15

摘要: 对激光冲击强化过程中激光参数的选择进行了优化。提出了基于人工神经网络的控制激光冲击强化效果的新方法,引入神经网络对试件经激光冲击后的表面质量类型进行识别。对2024-T62铝合金的研究及试验表明,采用该方法能够有效地提高合格试件的成品率。

关键词: 表面质量, 参数优选, 激光冲击强化, 神经网络, 效果控制

Abstract: An optimizing method of laser parameters is proposed. An artificial neural network (ANN) method for control of effect of laser shock-processing(LSP) is also proposed. A multilayered neural network is trained to identify types of surface quality of laser shock – processing zones. From the verification of aluminium alloy 2024 – T62,it is proved that this method could make the rate of qualified parts after LSP improve effectively.

Key words: Control of effect, Laser shock-processing(LSP), Neural network, Optimization of laser parameters, Surface qualities

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