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以激光功率P、光斑直径D、扫描速度V等为输入参数,非相变硬化处理、相变硬化处理和熔凝处理等为输出参数,对材料为20CrMo合金结构钢进行激光强化处理工艺控制优化研究。通过大量试验与计算机模拟分析和对比,建立了激光工作参数与材料表面强化关系的BP神经网络工艺优化模型。经过与实验数据的比较,运用该模型可以方便、准确地选择激光工艺参数,控制材料表面强化类别和保证工作表面的质量,真实反映了激光加工工艺规律。
The laser power P, spot diameter D, scanning speed V as the input parameters, non-phase-change hardening treatment, phase transformation hardening treatment and fusion treatment as the output parameters, the material is 20CrMo alloy structural steel laser strengthening process control optimization the study. Through a large number of experiments and computer simulation analysis and comparison, the BP neural network optimization model of the relationship between laser working parameters and material surface strengthening has been established. After comparison with the experimental data, the model can be used to select the laser process parameters conveniently and accurately, control the surface strengthening of the material and ensure the quality of the working surface, and truly reflect the laser processing technology.