TY - GEN
T1 - A Framework of Cognitive Intelligence-Enabled Welding Cyber Physical System
AU - Liu, Tianyuan
AU - Jiang, Yanan
AU - Zheng, Pai
AU - Bao, Jinsong
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023/8
Y1 - 2023/8
N2 - Building a welding cyber physical system (WCPS) is an important way to realize intelligent welding. However, the interaction between the current welding cyber world and the physical world is insufficient. On the one hand, it is reflected in the lack of cognition of the welding process that contains quality information. On the other hand, the interaction efficiency based on manual experience is low. A cognitive intelligence-enabled WCPS is proposed. Firstly, the welding knowledge graph is constructed to model and manage the multi-source data, so as to improve the interaction efficiency between welding cyber space and physical space. Secondly, the cognitive capability of the WCPS is improved through perceptual and cognitive computing. Finally, the welding action formed by each knowledge node is optimized based on reinforcement learning to improve the interactive capability of the WCPS.
AB - Building a welding cyber physical system (WCPS) is an important way to realize intelligent welding. However, the interaction between the current welding cyber world and the physical world is insufficient. On the one hand, it is reflected in the lack of cognition of the welding process that contains quality information. On the other hand, the interaction efficiency based on manual experience is low. A cognitive intelligence-enabled WCPS is proposed. Firstly, the welding knowledge graph is constructed to model and manage the multi-source data, so as to improve the interaction efficiency between welding cyber space and physical space. Secondly, the cognitive capability of the WCPS is improved through perceptual and cognitive computing. Finally, the welding action formed by each knowledge node is optimized based on reinforcement learning to improve the interactive capability of the WCPS.
UR - https://www.scopus.com/pages/publications/85174405975
U2 - 10.1109/CASE56687.2023.10260359
DO - 10.1109/CASE56687.2023.10260359
M3 - Conference article published in proceeding or book
AN - SCOPUS:85174405975
T3 - IEEE International Conference on Automation Science and Engineering
BT - 2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023
PB - IEEE Computer Society
T2 - 19th IEEE International Conference on Automation Science and Engineering, CASE 2023
Y2 - 26 August 2023 through 30 August 2023
ER -