首页|Studies from Tianjin University Have Provided New Data on Ma- chine Learning (Penetration Prediction of Narrow-gap Laser Weld- ing Based On Coaxial High Dynamic Range Observation and Ma- chine Learning)
Studies from Tianjin University Have Provided New Data on Ma- chine Learning (Penetration Prediction of Narrow-gap Laser Weld- ing Based On Coaxial High Dynamic Range Observation and Ma- chine Learning)
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NETL
NSTL
Elsevier
Investigators publish new report on Machine Learning. According to news originating from Tianjin, People's Republic of China, by NewsRx correspondents, research stated, "Narrow-gap laser welding is a novel joining process for thick-walled applications. However, it is challenging to obtain accurate root weld penetration as a crucial parameter for evaluating welding quality due to the limited spatial position." Funders for this research include National Natural Science Foundation of China (NSFC), Natural Science Foundation of Tianjin. Our news journalists obtained a quote from the research from Tianjin University, "The images of the front-side weld pool are one of the most effective signals for reflecting the root weld penetration. Hence, this paper proposes using a high dynamic range (HDR) camera to capture the weld pool morphology under narrow-gap laser welding. The characteristics of weld pool under different root weld penetration states are obtained and analyzed through orthogonal experiments. Furthermore, the root weld penetration states prediction model is constructed based on a backpropagation (BP) neural network."
TianjinPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningTianjin University
NETL
NSTL
Elsevier
