Touch Panel Metal Mesh Defect Detection via Capacitive Coupling

The detection device segments the metal mesh into multiple detection regions with different detection densities. High-density detection is applied to critical areas such as branch paths and intersection points, while low-density detection is used for less critical areas. This segmentation allows the system to improve detection reliability in key areas without proportionally increasing overall device complexity.

The patent implements local quality by applying different detection strategies to different parts of the metal mesh. Branch paths and intersection points receive enhanced detection with higher signal frequency and multiple detection angles, while main paths use standard detection. This localized enhancement of detection quality improves overall reliability without requiring uniform high-complexity detection across the entire mesh.

The detection device performs preliminary action by first conducting a rapid low-density scan to identify potential defect regions, then automatically triggering high-density precision detection only in those specific areas. This two-stage approach maintains high productivity through the initial fast scan while achieving high measurement precision in defect localization through the subsequent focused detailed detection.

The system dynamically adjusts detection parameters based on real-time findings. When a potential defect is detected during the initial scan, the system automatically increases detection frequency, changes detection angles, and concentrates detection resources on that specific region. This dynamic adaptation allows the system to maintain high overall detection speed while achieving precise defect positioning when needed.

The patent applies another dimension by introducing multi-angle detection and three-dimensional signal analysis specifically for branch path detection. Instead of only horizontal scanning, the system incorporates vertical angle variations and depth information to detect defects in the complex three-dimensional structure of branch paths. This dimensional enhancement improves detection precision for branch paths without requiring complete redesign of the entire detection system.

The system uses signal processing algorithms and data fusion techniques as intermediaries to enhance branch path detection. Multiple detection signals from different angles and frequencies are processed and fused to extract defect information from the complex branch path structure. This intermediary processing layer enables high-precision branch path detection without directly increasing the physical complexity of the detection hardware.