A large paper tube surface defect laser detection system

CN121917568BActive Publication Date: 2026-05-29XIAMEN YAMA RIBBONS & BOWS
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
XIAMEN YAMA RIBBONS & BOWS
Filing Date
2026-03-24
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing technologies are insufficient to effectively identify hidden defects in complex multilayer composite materials during the production of high-performance roll materials, leading to the risk of tube bursting under high-tension winding. Furthermore, the static threshold determination mechanism cannot adapt to dynamic and variable working conditions and cannot accurately assess the loss of load-bearing capacity.

Method used

A laser detection system is used to acquire three-dimensional point cloud data. Combined with three-dimensional topological feature extraction and a lightweight neural network model, the amplification factor of local stress concentration is calculated to generate a load-bearing capacity loss index. The system then outputs equipment control commands through a health rating and feedback module to achieve closed-loop linkage control.

Benefits of technology

Accurately identify hidden defects, avoid the risk of pipe bursts, maximize the carrying capacity of qualified products at the edge, ensure the safety and efficiency of the production line, and adapt to dynamic changes in operating conditions.

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Abstract

The present application relates to the technical fields of intelligent manufacturing and machine vision defect detection, and particularly relates to a large paper tube surface defect laser detection system, comprising: a data acquisition module, used for acquiring three-dimensional point cloud data of the large paper tube surface, and receiving paper tube process parameters and application working condition parameters; a three-dimensional topological feature extraction module, used for three-dimensional geometric features including defect depth gradient and defect long axis strike angle; a stress concentration deduction module, used for inputting the three-dimensional geometric features and the paper tube process parameters into a preset mechanical mapping model, and calculating a local stress concentration amplification multiple; a bearing capacity loss evaluation module, used for combining the local stress concentration amplification multiple, a preset paper tube basic yield strength and the application working condition parameters, and calculating a bearing capacity loss index; a health degree rating and feedback module, used for outputting equipment control instructions to a winding equipment according to the paper tube health degree rating; the present application ensures that the shape force mapping model can be long-term fitted to actual working condition changes of a production line.
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