一种生箔机流量自动化控制系统
By extracting texture information from X-ray intensity signals in the foil-making machine and combining it with a convolutional neural network model, the problem of capturing nonlinear relationships in the flow control of the foil-making machine was solved, and the thickness uniformity and microstructure of copper foil products were optimized, thereby improving production efficiency and product quality.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUNAN LONGZHI NEW MATERIAL TECH CO LTD
- Filing Date
- 2025-11-27
- Publication Date
- 2026-07-17
AI Technical Summary
The flow control of existing foil production machines relies on manual experience or simple closed-loop control, which cannot effectively capture the complex nonlinear relationship between flow and quality indicators, resulting in abnormal thickness uniformity and microstructure of copper foil products, causing a large amount of rework and waste.
By extracting texture information from X-ray intensity signals and combining it with convolutional neural network models and thickness indicators, a copper foil texture coefficient inversion module and a flow rate optimization module are constructed to achieve the adjustment of the strong nonlinear and spatiotemporal coupling characteristics between flow rate, thickness, and texture information in copper foil production.
This has achieved stability and consistency in the quality of copper foil products, shortened the lag time for flow rate adjustment, ensured the thickness uniformity and microstructure optimization of copper foil products, and improved production efficiency and product quality.
Smart Images
Figure CN121559875B_ABST
Abstract
Citation Information
Patent Citations
CN113198591A
CN115185191A