Laser cutting of metals has become the reference manufacturing technology in sheet metal working thanks to the flexibility and the increased productivity it offers when compared with other competitive technologies. Considering, in particular, the fusion-cutting mode, i.e., when nitrogen is used as an assisting gas, different aspects contribute to the process quality among which dross attachment plays the most important role. To cope with the related time-dependent deterioration of the process quality and to obtain an online adaptation of the process parameters for different working conditions, a closed-loop dross regulation system is needed. To realize it, a reliable, continuous, and accurate estimation of the dross is mandatory. This work focuses on this challenging problem, presenting and comparing different approaches to estimate the dross attachment based on the process emission collected by a coaxial camera. Specifically, a method which relies on the accurate analysis of the process emissions for determining an effective classification method is compared with a deep-learning approach based on convolutional neural networks. The obtained results, validated in real experimental conditions, confirm the possibility to accurately estimate the presence of significant dross attachment in real-time and open the way to the design of a closed-loop control algorithm for the real-time regulation of the dross attachment formation and consequently of the process quality.

中文翻译：

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基于过程排放图像的激光切割过程中浮渣附着的实时连续估计

与其他竞争技术相比，激光切割金属具有灵活性和更高的生产率，已成为钣金加工的参考制造技术。尤其考虑到熔断模式，即当使用氮气作为辅助气体时，不同方面对工艺质量有影响，其中浮渣附着起着最重要的作用。为了应对过程质量随时间的相关恶化，并获得不同工作条件下过程参数的在线适应，需要一个闭环浮渣调节系统。要实现这一点，必须对熔渣进行可靠、连续和准确的估算。这项工作的重点是这个具有挑战性的问题，介绍和比较基于同轴相机收集的过程排放来估计浮渣附着的不同方法。具体而言，将依赖于对过程排放的准确分析来确定有效分类方法的方法与基于卷积神经网络的深度学习方法进行比较。获得的结果在实际实验条件下得到验证，证实了实时准确估计显着浮渣附着存在的可能性，并为设计用于实时调节浮渣附着的闭环控制算法开辟了道路形成，从而影响工艺质量。将依赖于过程排放的准确分析来确定有效分类方法的方法与基于卷积神经网络的深度学习方法进行比较。获得的结果在实际实验条件下得到验证，证实了实时准确估计显着浮渣附着存在的可能性，并为设计用于实时调节浮渣附着的闭环控制算法开辟了道路形成，从而影响工艺质量。将依赖于过程排放的准确分析来确定有效分类方法的方法与基于卷积神经网络的深度学习方法进行比较。获得的结果在实际实验条件下得到验证，证实了实时准确估计显着浮渣附着存在的可能性，并为设计用于实时调节浮渣附着的闭环控制算法开辟了道路形成，从而影响工艺质量。