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激光加工质量与激光加工参数之间是一种复杂的非线性变化关系,传统方法无法准确拟合两者之间的变化关系,为了提高激光加工精度,针对激光加工参数优化问题,提出一种数据挖掘技术的激光加工参数优化模型。首先收集激光加工质量与激光加工参数的样本,然后采用数据挖掘技术支持向量机捕捉激光加工质量与激光加工参数之间的联系,并通过量子粒子群算法对支持向量机参数进行选择,建立激光加工参数优化模型,最后采用仿真实验对其性能进行测试,实验结果表明,数据挖掘技术有效地解决了激光加工过程中参数优化问题,使得激光加工质量更加满足实际生产需求。
Laser processing quality and laser processing parameters is a complex nonlinear relationship between the traditional methods can not accurately fit the relationship between the two changes, in order to improve the laser processing accuracy, laser processing parameters optimization, a data Optimization Model of Laser Processing Parameters of Excavation Technology. Firstly, the samples of laser processing quality and laser processing parameters were collected, then the relationship between laser processing quality and laser processing parameters was captured by using data mining support vector machine, and the parameters of support vector machine were selected by quantum particle swarm optimization algorithm to establish laser processing Finally, a simulation experiment is carried out to test its performance. The experimental results show that the data mining technology can effectively solve the problem of parameter optimization in the laser processing, making the laser processing quality more meet the actual production requirements.