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The International Journal of Advanced Manufacturing Technology
Erschienen in: The International Journal of Advanced Manufacturing Technology 5-6/2020

24.08.2020 | ORIGINAL ARTICLE

Optimization of dilution rate of laser cladding repair based on deep learning

verfasst von: Shichao Zhu, Wenliang Chen, Xiaohong Zhan, Liping Ding, Erhua Wang

Erschienen in: The International Journal of Advanced Manufacturing Technology | Ausgabe 5-6/2020

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Abstract

During the laser cladding repair, the heat accumulation effect is produced due to the continuous input of energy, which leads to the increase of dilution rate under the same process parameters. In order to get the appropriate dilution rate, an accurate finite element model was established based on the experiment, and the variation of dilution rates under different power functions was analyzed. According to the results of finite element analysis, different power functions and dilution rates at different times were collected, and the dilution rate was optimized through deep learning, and the ideal power function was obtained. The results show that the dilution rate of the whole cladding layer fluctuates around the ideal value all the time by adjusting the laser power in real time, and the results are satisfactory. The maximum error of dilution rate is 21.75%, the minimum error is 0, and the average error is 5.79%.
Vorheriger Artikel Effects of stepped cylindrical electrode in electrical discharge machining of blind holes
Nächster Artikel Reshaping diagrams for bending straightening of forged aeronautical components

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Metadaten
Titel
Optimization of dilution rate of laser cladding repair based on deep learning
verfasst von
Shichao Zhu
Wenliang Chen
Xiaohong Zhan
Liping Ding
Erhua Wang
Publikationsdatum
24.08.2020
Verlag
Springer London
Erschienen in
The International Journal of Advanced Manufacturing Technology / Ausgabe 5-6/2020
Print ISSN: 0268-3768
Elektronische ISSN: 1433-3015
DOI
https://doi.org/10.1007/s00170-020-05969-5

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