Closed-loop alignment identification with adaptive probing signals
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Solution Overview
Problem
Conventional cross direction (CD) alignment identification techniques in web manufacturing systems are inefficient as they require suspending the feedback CD controller, lack control over web qualities during testing, and often rely on manual observation of misalignment symptoms, which disrupts normal system operation.
Innovation Solution
A closed-loop alignment identification method using adaptive probing signal design that perturbs actuators with signals based on both spatial and dynamic characteristics of the web manufacturing system, allowing for continuous alignment testing without interrupting normal operations and enabling proactive misalignment detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If open-loop bump or step tests are used for CD alignment identification, then alignment parameters can be identified, but normal system operation is interrupted and web quality control is lost
Solution Approach 1:
The patent implements continuous alignment identification by integrating probing signal generation and analysis into the ongoing closed-loop control process. The system continuously generates probing signals, collects web quality measurements, and updates alignment parameters without interrupting normal production operations, enabling uninterrupted alignment monitoring and adjustment
Solution Approach 2:
The system uses real-time feedback from web quality measurements to continuously refine alignment identification. The closed-loop architecture feeds measurement data back to the alignment identification algorithm, allowing the system to adapt and update alignment parameters based on actual process conditions while maintaining normal operation
2Loss of information
If open-loop tests are performed, then alignment data can be collected, but there is no control over web qualities during testing
Solution Approach 1:
The closed-loop system continuously monitors web quality parameters during alignment identification and uses this feedback to maintain quality within acceptable ranges. The real-time measurement and control loop ensures that alignment data collection does not compromise web quality, as the system can immediately adjust actuators to correct any quality deviations
3Difficulty of detecting and measuring
If manual observation of misalignment symptoms is required, then alignment issues can be detected, but the process requires user intervention and is less efficient
Solution Approach 1:
The system performs self-diagnosis and self-adjustment by automatically detecting misalignment conditions through continuous probing signals and web quality measurements. The alignment identification algorithm autonomously analyzes the collected data, identifies misalignment issues, and triggers corrective actions without requiring manual observation or user intervention, fully automating the alignment maintenance process
Data Source
AI summary
A method includes designing probing signals for testing an alignment of actuators in a web manufacturing or processing system with measurements of a web of material being manufactured or processed by the system. The method also includes providing the probing signals during alignment testing to identify the alignment of the actuators with the measurements of the web. Designing the probing signals includes designing the probing signals based on both spatial and dynamic characteristics of the web manufacturing or processing system.