Countersink Depth Inspection for Vision-Guided Aircraft Panel Drilling
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Solution Overview
Problem
Current methods for countersinking predrilled holes in aircraft panels are inefficient, requiring large workforces, expensive machine tools, and often result in panel deflection and repetitive strain injuries for human operators, while bespoke fixtures are costly and not scalable for various panel shapes.
Innovation Solution
An apparatus and method using industrial robots with a camera and processors to accurately determine the depth of countersinks by capturing images, detecting edges, calculating diameters and angles, and adjusting cutting tools to ensure precise and consistent countersinking, reducing the need for expensive fixtures and minimizing operator strain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual countersinking by human operators is used, then flexibility in handling various panel shapes is maintained, but productivity is low and operators develop repetitive strain injuries
Solution Approach 1:
The patent replaces manual mechanical countersinking operations with an automated robotic system that uses vision guidance and force control. The robot equipped with a force sensor and camera can automatically adapt to different panel shapes and orientations, eliminating repetitive strain on human operators while maintaining flexibility through programmable motion control and real-time image processing.
Solution Approach 2:
The system enables the workpiece to guide the cutting process through vision acquisition of panel features and automatic feature detection. The robot autonomously determines the optimal countersinking position and orientation by detecting panel edges and curvature, reducing the need for human intervention and increasing productivity.
2Manufacturing precision
If machine tools with secure fixtures are used, then panel deflection is prevented, but device complexity and cost increase significantly
Solution Approach 1:
The patent replaces complex mechanical fixtures with a vision-guided robotic system that uses force sensors to detect panel curvature and automatically adjusts the countersinking operation. The camera acquires images of the panel surface, and the system processes these images to determine the optimal cutting position and angle, eliminating the need for expensive bespoke fixtures while maintaining manufacturing precision.
Solution Approach 2:
The system dynamically changes operational parameters based on real-time panel characteristics. By detecting panel curvature and orientation through vision systems, the robot adjusts cutting depth, speed, and angle to compensate for panel deflection, achieving precise countersinking without requiring rigid mechanical constraints.
3Manufacturing precision
If bespoke fixtures are designed for each panel shape, then manufacturing precision is improved, but manufacturing cost and time increase
Solution Approach 1:
The patent implements a universal robotic system that can handle multiple panel shapes and sizes through vision guidance and adaptive control. The single robot equipped with force sensors and cameras can be programmed to work with various panel configurations, eliminating the need to manufacture separate bespoke fixtures for each panel type while maintaining high countersinking accuracy through real-time image processing and feature detection.
Solution Approach 2:
The system creates a digital representation of the panel geometry through vision acquisition and edge detection. By processing images to identify panel features and curvature, the system generates a virtual model that guides the countersinking operation, replacing the need for physical custom fixtures with a software-based adaptive approach.
Data Source
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AI summary
Disclosed is a method and apparatus for determining a depth of a feature (4) formed in an object (2), the feature (4) having been formed in the object (2) by a cutting tool (38). The apparatus comprises: a camera (42) configured to capture an image of the feature (4) and a portion of the object (2) proximate to the feature (4); and one or more processors operatively coupled to the camera (42) and configured to: detect, in the image, an edge (72) of the feature (4) between the feature (4) and a surface of the object (2); using the detected edge (72), calculate a diameter for a circle (74, 76, 78); acquire a point angle of the cutting tool (38); and, using the calculated diameter and the acquired point angle, calculate a depth value for the feature (4).