Robotic Dark-Field Imaging for Curved Worksurface Inspection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing industrial processes face challenges in detecting and correcting defects on worksurfaces during material application due to curvature, sharp features, and irregularities, leading to subjective quality control and potential defects in products.
Innovation Solution
The implementation of imaging systems that utilize line-scan array technology and distance sensors to capture images in near-dark or dark field modes, allowing for precise topography mapping and defect detection on curved or irregular surfaces, with robotic control for real-time inspection and repair.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional imaging systems are used for surface inspection, then the system structure is simple, but the measurement precision and defect detection capability are insufficient due to curvature and irregularities
Solution Approach 1:
The imaging system is mounted on a robotic arm that dynamically adjusts its position and orientation to maintain optimal imaging conditions. The system continuously adapts to surface curvature by moving the camera and light source together, keeping them at a fixed relative position while following the surface contours, thereby maintaining high measurement precision on irregular surfaces
Solution Approach 2:
The system transitions from 2D surface imaging to 3D topography mapping by incorporating depth information through stereo vision or focus variation techniques. This dimensional enhancement allows the system to capture surface curvature and irregularities, improving defect detection precision on non-planar surfaces
2Adaptability or versatility
If the imaging system maintains a fixed distance from the surface, then the image quality is consistent, but the system cannot adapt to curved or irregular surfaces
Solution Approach 1:
The robotic arm dynamically adjusts the imaging system's position to follow surface contours while maintaining a constant distance from the surface. This dynamic adaptation allows the system to handle curved and irregular surfaces while preserving image quality consistency through real-time position control
Solution Approach 2:
The system uses real-time feedback from surface scanning to adjust the robotic arm's position and the imaging system's orientation. This closed-loop control ensures the camera maintains optimal distance and angle relative to the surface, adapting to curvature while preserving image quality through continuous correction
3Measurement precision
If dark field imaging mode is used, then the defect detection capability is improved, but the lighting complexity and energy consumption increase
Solution Approach 1:
The lighting system provides localized illumination at specific angles relative to the surface normal, creating dark field conditions only in the regions where defects are most likely to occur. This selective lighting approach improves defect detection capability while reducing overall energy consumption by illuminating only necessary areas
Solution Approach 2:
The system dynamically adjusts lighting parameters such as intensity, angle, and duration based on surface characteristics and defect probability. By changing these parameters adaptively, the system achieves high defect detection capability while optimizing energy consumption through reduced illumination in low-risk areas
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
Enables objective quality control and rapid defect detection and correction, improving the production of high-fidelity images and reducing manual intervention, thereby enhancing the quality and efficiency of surface processing.
Implementation Method 1
capturing image data of the surface. The image data is captured in a near dark field mode or a dark field image mode
Data Source
AI summary
A method of evaluating a surface is presented that includes imaging the surface, with an imaging system. Imaging includes providing a camera of the imaging system proximate the surface. Imaging also includes causing the imaging system and the surface to move relative to each other, such that a distance between the imaging system and the surface is substantially maintained. Imaging also includes capturing image data of the surface. The image data is captured in a near dark field mode or a dark field image mode. The method also includes analyzing the image data and detecting a topography and/or appearance of the surface. The method also includes generating an evaluation regarding the surface based on the detected topography and/or surface appearance.