Automated 3D Hole Edge Detection Using Structured Light and Point Clouds
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Solution Overview
Problem
Current methods for measuring 3D holes are time-consuming and lack accuracy, especially when dealing with numerous holes, as they rely on manual plug gauges and contact-based measurements, which are inefficient and prone to inconsistency.
Innovation Solution
A method utilizing 2D image data and 3D point cloud data to rapidly and accurately measure hole edges by defining contours, sampling data points, and connecting turning points to determine the hole edge, leveraging reflection intensity information to estimate hole positions and reduce data processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual plug gauge measurement is used for 3D holes, then measurement can be performed with simple equipment, but measurement time increases significantly and accuracy decreases when measuring numerous holes
Solution Approach 1:
The patent replaces the manual mechanical plug gauge measurement system with an automated optical measurement system using structured light projection and image capture. The system projects structured light patterns onto the workpiece surface, captures the deformed light patterns with a camera, and automatically processes the images to extract hole measurements, eliminating manual intervention and significantly improving both speed and accuracy.
Solution Approach 2:
The patent creates a digital copy of the physical hole geometry by capturing structured light patterns and processing them into point cloud data and contour information. This digital replica allows for rapid, repeated measurements without physical contact, enabling full inspection of numerous holes with consistent accuracy and minimal measurement time.
2Measurement precision
If different people perform manual measurement of 3D holes, then flexibility in operation is maintained, but measurement accuracy becomes inconsistent
Solution Approach 1:
The measurement system performs self-measurement by automatically capturing structured light patterns, processing the images through algorithms to identify hole contours and turning points, and generating measurement results without human intervention. This automated self-service approach ensures consistent, repeatable measurements across all holes regardless of operator variability.
Solution Approach 2:
The patent replaces human operators with an automated optical measurement system that uses structured light projection and image processing algorithms. This substitution eliminates the inconsistency introduced by different people performing measurements while maintaining the ability to measure various hole types and geometries.
3Reliability
If full inspection of all holes is performed, then measurement completeness is improved, but measurement time increases significantly
Solution Approach 1:
The system performs continuous measurement of all holes in the field of view by capturing the entire workpiece surface with structured light patterns in a single or few captures. The image processing algorithm continuously analyzes the captured data to identify all hole contours and turning points, enabling complete inspection of numerous holes simultaneously rather than sequentially, thus maintaining high inspection completeness while minimizing measurement time.
4Measurement precision
If 3D point cloud data is processed to obtain hole measurements, then measurement accuracy is improved, but data processing time increases
Solution Approach 1:
The patent segments the processing task by first identifying candidate hole regions in the image, then focusing detailed 3D point cloud analysis only on those segmented regions. The algorithm divides the workpiece surface into relevant and irrelevant areas, processing only the relevant regions containing holes to extract precise edge measurements, thereby maintaining high accuracy while significantly reducing overall data processing time.
Solution Approach 2:
The system performs preliminary processing by capturing 2D images and identifying hole candidate regions before conducting detailed 3D point cloud analysis. This preliminary action filters out non-hole areas and pre-positions the analysis on relevant regions, reducing the volume of 3D data that requires intensive processing while ensuring accurate hole edge measurement.
Data Source
AI summary
A method for measuring a hole provided in a workpiece is provided and the method comprises: obtaining a three-dimensional point cloud model of the workpiece and a two-dimensional image of the workpiece, defining a first contour in the three-dimensional point cloud model based on an intensity difference of the two-dimensional image, defining a second contour and a third contour respectively based in the first contour, bounding a data point testing region between the second contour and the third contour, respectively defining data point sampling regions along a plurality of cross-section directions of the data point testing region, respectively sampling data points in the data point sampling regions to obtain a turning point set comprising turning points, wherein each of the turning points has the largest turning margin, connecting the turning points which are distributed in the turning point set along a ring direction to obtain an edge of the hole.