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

被引:6
|
作者
Sun, Tao [1 ,2 ]
Mei, Xuesong [1 ,2 ]
Sun, Xiaomao [1 ,2 ]
Cai, Yuxin [1 ,2 ,3 ]
Ji, Yichun [1 ,2 ]
Fan, Zhengjie [1 ,2 ]
机构
[1] Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian 710049, Peoples R China
[2] Xi An Jiao Tong Univ, Shaanxi Key Lab Intelligent Robots, Xian 710049, Peoples R China
[3] Nanyang Technol Univ, Sch Mech & Aerosp Engn, Singapore 639798, Singapore
基金
中国国家自然科学基金;
关键词
Machine learning; process control; real-time monitoring; sequential three-way decision (S3WD); support vector machine (SVM); ultrafast laser drilling (ULD); FEATURE-SELECTION; MECHANISM;
D O I
10.1109/TII.2022.3165302
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:5422 / 5432
页数:11
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