倔强一点
发表于 2025-3-23 10:13:37
Penetration Prediction with Machine Learning Models, usually requires a sensor on the back of the weldment which is not practical in many welding applications. In the manual welding process, the geometry of weld pool top surface geometry is a major reference for welder to determine the penetration condition. This chapter focuses on establishing an ar
飞镖
发表于 2025-3-23 16:48:53
Penetration Detection of Narrow U-Groove Welding,ation for the butt joint weld. By filling a groove design joint makes it possible to weld the workpieces with less heat input. The root pass weld is the first weld performed on the root of the groove joint. To perform a high-quality weld, the first pass of the weld should fully penetrate the root fa
eczema
发表于 2025-3-23 22:03:04
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Indelible
发表于 2025-3-24 00:52:13
https://doi.org/10.1007/978-981-15-6491-8Intelligent Welding; Robotic Welding; Optical Sensing; Machine Learning; Adaptive Control; Feature Extrac
眼界
发表于 2025-3-24 03:51:36
Zongyao Chen,Zhili Feng,Jian ChenProvides a comprehensive overview of non-destructive methods for detecting and reducing welding defects during gas tungsten arc welding (GTAW) based on computer vision and artificial intelligence.Pres
Insatiable
发表于 2025-3-24 09:19:39
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bacteria
发表于 2025-3-24 11:23:16
978-981-15-6493-2Springer Nature Singapore Pte Ltd. 2021
节约
发表于 2025-3-24 16:52:04
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不安
发表于 2025-3-24 20:34:38
Conclusions and Recommendations,ld pool geometry is the major source of information related to the formation of these defects. In this dissertation, a new visual sensing and control system was developed to eliminate the welding defects during GTAW.
咯咯笑
发表于 2025-3-25 02:28:30
Monitoring Weld Pool Surface with Active Vision Image,In this chapter, a new weld pool monitoring system was established with laser light illumination, allowing us to observe the dynamic weld pool geometry during welding. The weld pool dynamic behavior under different welding currents and speed ranges was studied.