Rewinder Log Imaging Control for High-Speed Winding Stability
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for assessing log formation during winding are manual and based on visual observations, leading to inefficiencies, reduced processing speeds, and increased operator intervention due to variability in winding processes, resulting in suboptimal machine efficiency and product quality.
Innovation Solution
The use of high-speed image capturing equipment and machine learning strategies to accurately determine log position, geometry, displacement, and vibration, enabling adaptive and predictive controls to optimize winding processes and reduce operator intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual visual observation methods are used to assess log formation, then operator intervention is simple and equipment complexity is low, but processing speed must be reduced to safe speeds and operator time consumption increases
Solution Approach 1:
The patent replaces manual visual observation with an automated image capture system using cameras and image processing algorithms. The system captures images of the log during winding, processes them to detect log position, diameter, and formation characteristics, and provides automated feedback control. This substitution eliminates the need for operators to manually observe and adjust parameters, enabling higher processing speeds while maintaining or improving log quality.
2Reliability
If conservative safe speeds are used to avoid vibration and quality issues, then product quality is maintained, but machine productivity decreases significantly
Solution Approach 1:
The patent implements a feedback control system where images of the log are captured during winding, processed to detect log formation characteristics and vibration, and used to provide real-time feedback for adjusting winding parameters. This closed-loop feedback enables the system to operate at higher speeds while automatically detecting and correcting quality issues, rather than relying on conservative fixed speed limits.
Solution Approach 2:
The system performs preliminary detection of log formation characteristics and potential quality issues before they become critical problems. By capturing and analyzing images continuously during winding, the system can identify trends and make preemptive adjustments to prevent quality degradation, allowing operation at higher speeds without sacrificing reliability.
3Ease of operation
If pre-programmed adjustments based on assumed criteria are used, then operator time is reduced, but adjustments may be inapplicable for particular conditions and measurement precision decreases
Solution Approach 1:
The system performs self-assessment by automatically capturing images, processing them through image recognition algorithms, and determining log formation characteristics without operator intervention. The system serves itself by making real-time adjustments based on actual measured conditions rather than relying on pre-programmed assumptions or general criteria, thereby achieving both automated operation and high measurement precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances converting line performance by minimizing operator intervention, optimizing uptime, and increasing processing speeds while maintaining product quality, by providing real-time feedback and adaptive control signals based on predictive image-related information.
Implementation Method 1
an image capture device associated with a log being wound in a winding nest of a rewinding machine
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A converting line includes a rewinding machine for winding web material into a log. For time points during a time period of the log wind cycle, predictive information representative of a log to be wound is generated and stored in a memory of a control of the rewinding machine. An image capture device is enabled to capture a plurality of images of the log being wound in the winding nest at the plurality of corresponding time points during the time period. Log image capture information is generated based upon the plurality of captured images and corresponding time points during the time period. The log image capture information is compared with the generated predictive log image information to determine a difference in log image. Revised predictive log image information is generated based at least in part upon a difference in the log image capture information relative to predictive log image information.