Selective assembly of rolling element bearings based on pointer network
ID：169
Submission ID：163 View Protection：ATTENDEE
Updated Time：2024-10-23 10:02:36 Hits：38
Poster Presentation
Start Time：Pending （Asia/Shanghai）
Duration：Pending
Session：[No Session] » [No Session Block]
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Abstract
Radial clearance is an important quality indicator for deep groove ball bearings and cylindrical roller bearings. Given a batch of components, including outer rings, inner rings and rolling elements, with different sizes due to the manufacturing error, selective assembly is a critical process to properly combine these components to obtained qualified bearings as many as possible. In this work, a method based on pointer network is proposed to address the precise selective assembly of bearing components. A graph embedding layer is employed to model all the components as graph nodes and their possible relationship as edges. The pointer network is trained to generate a sequence representing the assembly relationship of components, with the objective of maximizing the assembly rate and minimizing the bias with respect to the best clearance. Compared with traditional intelligent optimization method, such as genetic algorithm, which can also be used to approximate solutions for the selective assembly of bearing components, the proposed method outperforms with better generalization capability, it can be trained using a small-batch of data and be applied for a much large batch problem without losing accuracy and significant increasing the computational time.
Keywords
Rolling element bearings,selective assembly,clearance,point network
Speaker
YangZhe
Prof. Dongguan University of TechnologySubmission Author
All comments
15th August 2024 31st August 2024- Manuscript Submission
15th September 2024 - Acceptance Notification
1st October 2024 - Camera Ready Submission
1st October 2024 – Early Bird Registration
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