Robotic Non-Destructive Inspection of Aircraft. Phase 1.

Abstract

Non-Destructive Inspection (NDI) of aircraft is known to be a time consuming, boring, and an error prone task for human inspectors. A method is needed for looking (inspecting) at an aircraft without reliability problems due to boredom while minimizing aircraft total inspection time during the life of the aircraft. The application of robotics to the Non-destructive Inspection (NDI) of aircraft was investigated. It was found that it is feasible to transform the Navy's robotic deriveter to a neural network based NDI robot. A feedforward multilayer neural network was found to be very reliable at detecting cracks around rivets. In addition, an efficient new manipulator path planning method using neural networks was found to be useful for the robotic aircraft NDI.

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Document Details

Document Type
Technical Report
Publication Date
Sep 05, 1991
Accession Number
ADA240777

Entities

People

  • Joel Davis

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Aircrafts
  • Airframes
  • Brushless Dc Motors
  • Computer Vision
  • Computers
  • Control Systems
  • Detection
  • Detectors
  • Geometry
  • Image Processing
  • Motion Planning
  • Neural Networks
  • Robots
  • Three Dimensional
  • Tools
  • Two Dimensional

Fields of Study

  • Engineering

Readers

  • Facility/Structural Engineering.
  • Robotics and Automation.
  • Structural Health Monitoring of Composite Structures.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Neural Networks
  • Autonomy