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A Visual Measurement Method for Deep Holes in Composite Material Aerospace Components.

Fantong Meng1, Jiankun Yang2, Guolin Yang1

  • 1State Key Laboratory of High-Performance Precision Manufacturing, Dalian University of Technology, Dalian 116024, China.

Sensors (Basel, Switzerland)
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PubMed
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This study presents a new visual measurement method for accurately detecting deep holes in composite materials, crucial for aerospace assembly. The technique enhances hole edge features, achieving high precision for critical component alignment.

Keywords:
Laplace operatorcomposite materialsimage processingrobotic assembly

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Area of Science:

  • Materials Science
  • Robotics
  • Computer Vision

Background:

  • Accurate visual measurement of deep holes in composite materials is essential for aerospace component assembly.
  • Challenges include complex surface textures and imaging interference, hindering precise hole detection.
  • Positional accuracy of assembly holes directly affects the quality of assembled aerospace components.

Purpose of the Study:

  • To develop an advanced visual measurement method for deep holes in composite materials.
  • To overcome limitations in detecting holes due to surface complexity and imaging interference.
  • To improve the accuracy and reliability of hole detection for robotic assembly applications.

Main Methods:

  • Proposed a novel visual measurement method utilizing a radial penalty Laplacian operator.
  • The operator suppresses visual noise and enhances the distinct features of hole edges.
  • Implemented a unique inflection-point-removal algorithm to refine hole edge detection.

Main Results:

  • Successfully detected deep holes (10 mm diameter, 50 mm depth) in composite material components.
  • Achieved a high measurement precision of 0.03 mm for the detected holes.
  • Demonstrated the method's effectiveness in complex composite material environments.

Conclusions:

  • The proposed radial penalty Laplacian operator and inflection-point-removal algorithm offer a robust solution for deep hole visual measurement.
  • This method significantly enhances the accuracy of hole detection in challenging composite materials.
  • The findings contribute to improved quality control and efficiency in aerospace robotic assembly.