Laser cladding path planning for gear repair based on area division and trajectory correction.
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| Title: | Laser cladding path planning for gear repair based on area division and trajectory correction. |
|---|---|
| Authors: | Huang, Hanlin1 (AUTHOR), Zhou, Li1 (AUTHOR), Luo, Shanming1 (AUTHOR) smluo@jmu.edu.cn |
| Source: | International Journal of Advanced Manufacturing Technology. Oct2024, Vol. 134 Issue 7/8, p3719-3732. 14p. |
| Subjects: | Convolutional neural networks, Manufacturing workstations, Ant algorithms, Laser ranging, Point cloud, Laser beams |
| Abstract: | In addressing the issues of laser defocusing, laser beam interference, and low melting efficiency prevalent in current gear laser cladding path planning, a method for gear laser cladding path planning is formulated based on area segmentation and trajectory refinement. Firstly, the tooth surface model is reconstructed using three times NURBS surfaces. Subsequently, the tooth failure region is extracted through point cloud data alignment and Boolean operations, and the laser scanning region is preliminarily delineated using a graphical convolutional neural network. This is further refined by employing an ant colony algorithm. Secondly, by employing a geometrically constrained mathematical model of the gear, the compensation distance for laser focusing and the feasible domain range of the laser beam are determined to effectuate the trajectory refinement for the gear's laser cladding. Finally, completing the laser scanning area division and trajectory correction to perform the laser cladding gear repair experiment, the experiment relies on the HLC40 laser powder feeding additive manufacturing workstation, adopting the YLR-4000IPG laser for cladding operation. The experimental results demonstrate the absence of focus offset and laser beam interference during the cladding process. Moreover, the total travel distance of the planned path was reduced by 9–12%, the cladding time was reduced by 8–16%, and the morphological quality of the cladding layer was improved by 39–46%. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Advanced Manufacturing Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 179605348 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Laser cladding path planning for gear repair based on area division and trajectory correction. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Huang%2C+Hanlin%22">Huang, Hanlin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhou%2C+Li%22">Zhou, Li</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Luo%2C+Shanming%22">Luo, Shanming</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> smluo@jmu.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Advanced+Manufacturing+Technology%22">International Journal of Advanced Manufacturing Technology</searchLink>. Oct2024, Vol. 134 Issue 7/8, p3719-3732. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Convolutional+neural+networks%22">Convolutional neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Manufacturing+workstations%22">Manufacturing workstations</searchLink><br /><searchLink fieldCode="DE" term="%22Ant+algorithms%22">Ant algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Laser+ranging%22">Laser ranging</searchLink><br /><searchLink fieldCode="DE" term="%22Point+cloud%22">Point cloud</searchLink><br /><searchLink fieldCode="DE" term="%22Laser+beams%22">Laser beams</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In addressing the issues of laser defocusing, laser beam interference, and low melting efficiency prevalent in current gear laser cladding path planning, a method for gear laser cladding path planning is formulated based on area segmentation and trajectory refinement. Firstly, the tooth surface model is reconstructed using three times NURBS surfaces. Subsequently, the tooth failure region is extracted through point cloud data alignment and Boolean operations, and the laser scanning region is preliminarily delineated using a graphical convolutional neural network. This is further refined by employing an ant colony algorithm. Secondly, by employing a geometrically constrained mathematical model of the gear, the compensation distance for laser focusing and the feasible domain range of the laser beam are determined to effectuate the trajectory refinement for the gear's laser cladding. Finally, completing the laser scanning area division and trajectory correction to perform the laser cladding gear repair experiment, the experiment relies on the HLC40 laser powder feeding additive manufacturing workstation, adopting the YLR-4000IPG laser for cladding operation. The experimental results demonstrate the absence of focus offset and laser beam interference during the cladding process. Moreover, the total travel distance of the planned path was reduced by 9–12%, the cladding time was reduced by 8–16%, and the morphological quality of the cladding layer was improved by 39–46%. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Advanced Manufacturing Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00170-024-14390-1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 3719 Subjects: – SubjectFull: Convolutional neural networks Type: general – SubjectFull: Manufacturing workstations Type: general – SubjectFull: Ant algorithms Type: general – SubjectFull: Laser ranging Type: general – SubjectFull: Point cloud Type: general – SubjectFull: Laser beams Type: general Titles: – TitleFull: Laser cladding path planning for gear repair based on area division and trajectory correction. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Huang, Hanlin – PersonEntity: Name: NameFull: Zhou, Li – PersonEntity: Name: NameFull: Luo, Shanming IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 02683768 Numbering: – Type: volume Value: 134 – Type: issue Value: 7/8 Titles: – TitleFull: International Journal of Advanced Manufacturing Technology Type: main |
| ResultId | 1 |
