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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。
激光冲击强化效果的控制及人工神经网络预报研究
【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
【机 构】
：
江苏理工大学机械工程学院
【出 处】
：
机械工程学报
【发表日期】
：
2000年12期
【基金项目】
：
江苏省应用基金,,教育部博士点基金资助项目
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