Real-Time Control of Weld Pool Dynamics During Robotic GTAW

Chen, Shanben; Wu, Jing

doi:10.1007/978-3-540-85642-9_6

Cited by 4 publications

(1 citation statement)

References 27 publications

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“…Vision sensing technology possesses the benefits of simple equipment setup, mature supporting algorithms, and good stability. Therefore, visual sensors are widely used in fields such as weld recognition, weld tracking, molten pool monitoring, and weld quality monitoring [12,13]. As shown in Figure 3, according to the light source properties, the system can be divided into active and passive vision sensing.…”

Section: Vision Sensingmentioning

confidence: 99%

Review on the Application of the Attention Mechanism in Sensing Information Processing for Dynamic Welding Processes

Xu,

Liu,

et al. 2024

JMMP

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Arc welding is the common method used in traditional welding, which constitutes the majority of total welding production. The traditional manual and manual teaching welding method has problems with high labor costs and limited efficiency when faced with mass production. With the advancement in technology, intelligent welding technology is expected to become a solution to this problem in the future. To achieve the intelligent welding process, modern sensing technology can be employed to effectively simulate the welder’s sensory perception and cognitive abilities. Recent studies have advanced the application of sensing technologies, leading to the advancement in intelligent welding process. The review is divided into two aspects. First, the theory and applications of various sensing technologies (visual, sound, arc, spectral signal, etc.) are summarized. Then, combined with the generalization of neural networks and attention mechanisms, the development trends in welding sensing information processing and modeling technology are discussed. Based on the existing research results, the feasibility, advantages, and development direction of attention mechanisms in the welding field are analyzed. In the end, a brief conclusion and remarks are presented.

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Section: Vision Sensingmentioning

confidence: 99%