Real-Time Monitoring and Control of the Breakthrough Stage in Ultrafast Laser Drilling Based on Sequential Three-Way Decision

• Published in: IEEE transactions on industrial informatics 2023-04, Vol.19 (4), p.5422-5432
• Main Authors: Sun, Tao, Mei, Xuesong, Sun, Xiaomao, Cai, Yuxin, Ji, Yichun, Fan, Zhengjie
• Format: Article
• Language: English
• Subjects: Bias; Data processing; Delay time; Drilling; Emission analysis; Feature extraction; Laser drilling; Lasers; Machine learning; Monitoring; Optical communication; Optical pulses; Process control; Real time; real-time monitoring; sequential three-way decision (S3WD); Stimulated emission; support vector machine (SVM); Support vector machines; ultrafast laser drilling (ULD); Ultrafast lasers; Ultrafast optics
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2022.3165302

Real-time monitoring and control of breakthrough stage are essential issues in ultrafast laser drilling (ULD) process. This article proposed a novel intelligent methodology to address the decision bias problem in monitoring and control of breakthrough stage. Eight time-domain statistical features were extracted after analyzing the correlation between the optical emission signal and the drilling process and data processing. To build the identification model of breakthrough stage, support vector machine method was adopted and the identification accuracy can up to 98.42%. Even so, there is a large deviation between the prediction breakthrough time by the identification model and the actual breakthrough time, which can up to 3.81 s. Considering the decision bias, the comprehensive Gaussian weight sequential three-way decision (CGW-S3WD) method was proposed for the first time. Compared to the actual breakthrough time, the mean decision time is only delayed by 0.375 s based on the combination of the identification model and CGW-S3WD method under simulated conditions. Finally, the method was applied to monitoring and control of breakthrough stage in the actual ULD process. Experimental results demonstrate that the control delay time is only 0.354 s and the high-quality holes and protection of the back wall can be achieved simultaneously. The research confirms that the method can reduce the decision bias and provides a new perspective for accurate monitoring of complex industrial scenarios.