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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。
The selection of laser parameters during laser shock enhancement is optimized. A new method of controlling laser shock enhancement based on artificial neural network is proposed. The neural network is introduced to identify the surface quality of the specimen after laser shock. The research and experiment on 2024-T62 aluminum alloy show that the method can effectively improve the yield of the qualified test piece.