Analysis for Roll-bending Forming Quality of Spaceflight Thin-walled Cylindrical Workpieces Based on PointCPP-LSF Method. (English)
In: China Mechanical Engineering, Jg. 33 (2022-04-25), Heft 8, S. 977-985
academicJournal
Zugriff:
In order to solve the problems that the accuracy and speed requirements of the roll-bending forming quality detection for spaceflight thin-walled cylindrical workpieces might not be met due to the high dependence of the traditional cylindrical fitting method on the initial values of parameters, a PointCPP-LSF method was proposed to realize the analysis of spaceflight thin-walled cylindrical workpiece roll-bending forming quality. Based on point cloud deep learning, a point network for cylindrical parameter prediction (PointCPP) model was established to obtain reliable initial values, and then the cylindrical parameters were iteratively optimized based on the improved LSF method, and combined with the gross error elimination mechanism, the robust curvature radius calculation results were finally obtained. The experimental results show that the proposed method may effectively improve the accuracy and speed of roll-bending forming quality detection for spaceflight thin-walled cylindrical workpieces. [ABSTRACT FROM AUTHOR]
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Titel: |
Analysis for Roll-bending Forming Quality of Spaceflight Thin-walled Cylindrical Workpieces Based on PointCPP-LSF Method. (English)
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Autor/in / Beteiligte Person: | Qingbo, Al ; Jie, ZHANG ; Hui, CHENG ; Youlong, LYU ; Liling, ZUO ; Lan, HU |
Zeitschrift: | China Mechanical Engineering, Jg. 33 (2022-04-25), Heft 8, S. 977-985 |
Veröffentlichung: | 2022 |
Medientyp: | academicJournal |
ISSN: | 1004-132X (print) |
DOI: | 10.3969/j.issn.1004-132X.2022.08.013 |
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