Web Defect Detection Using Roll-Synchronized Repeat Analysis
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Solution Overview
Problem
Conventional web inspection systems struggle to accurately identify the source of repeating anomalies in moving webs, particularly when rolls with similar diameters are used, and fail to account for spatial distortion or undocumented roll changes, leading to difficulties in defect detection and maintenance.
Innovation Solution
An automated inspection system that uses optical acquisition devices and sophisticated algorithms to differentiate between repeating and random anomalies, correlating anomaly positions with roll synchronization signals to identify the source of repeating defects, and applies application-specific defect detection recipes based on product selection parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional web inspection systems are used to identify repeating defects, then defect detection capability is provided, but accuracy in identifying the source roll deteriorates when rolls have similar diameters
Solution Approach 1:
The system performs preliminary measurements of actual roll diameters and circumferences before defect analysis, storing this information for subsequent correlation with repeating defect patterns. This preliminary action enables accurate source identification even when rolls have nominally identical dimensions.
Solution Approach 2:
The patent replaces conventional mechanical assumption-based identification (assuming all rolls of nominal size X are identical) with optical/electronic measurement and computational correlation. Roll synchronization signals and actual dimensional measurements substitute for mechanical estimation methods.
2Reliability
If conventional inspection systems assume fixed roll diameters, then system simplicity is maintained, but reliability deteriorates when undocumented roll changes occur
Solution Approach 1:
The system continuously monitors roll synchronization signals and compares actual defect repeat distances with expected values based on recorded roll circumferences. When discrepancies are detected, the system can identify that a roll change has occurred and adjust accordingly, providing feedback that maintains reliability despite roll substitutions.
Solution Approach 2:
The inspection system automatically tracks and records roll parameters and synchronizes with roll positions without requiring external documentation or manual input. The system self-updates its understanding of roll characteristics through synchronization signals, eliminating the need for external parameter tracking.
3Measurement precision
If conventional systems ignore spatial distortion, then processing complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The system performs preliminary characterization of spatial distortion in the web path before defect analysis. By measuring and storing distortion parameters in advance, the system can compensate for spatial variations when correlating defect positions with roll positions, improving measurement accuracy.
4Measurement precision
If comprehensive defect analysis is performed at high web speed, then productivity is maintained, but measurement precision deteriorates due to reduced analysis time
Solution Approach 1:
The system performs preliminary defect detection and classification during high-speed web traversal, capturing essential anomaly information in real-time. More sophisticated analysis, including application-specific defect detection recipes, is then performed offline or at reduced speed, allowing comprehensive analysis without compromising production throughput.
Data Source
AI summary
Techniques are described for inspecting a web and controlling subsequent conversion of the web into one or more products. A system, for example, comprises an imaging device, an analysis computer and a conversion control system. The imaging device images the web to provide digital information. The analysis computer processes the digital information to identify regions on the web containing anomalies. The conversion control system subsequently analyzes the digital information to determine which anomalies represent actual defects for a plurality of different products. The web inspection system may preferentially apply different application-specific defect detection recipes depending on whether a given anomaly is a repeating or random anomaly.