An Intelligent Control Strategy for the Spray Forming Process

Abstract

A control system incorporating a fuzzy logic inference engine and optical sensors has been developed for the spray forming facility at the David Taylor Research Center. An imaging system employing laser illumination and a high speed CCD camera provides critical on-line preform surface roughness and rate of growth information. A fuzzy logic controller utilizes a rule set to translate visual information into a form that can be reviewed by the conditional statements of the rule base. A high performance manipulator and motion controller have also been incorporated into the spray forming system. This discussion includes development of optical sensors and integration of advanced control systems to determine and activate required corrective actions to the spray forming process parameters.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1991
Accession Number
ADA241290

Entities

People

  • Angela L. Moran
  • Craig J. Madden
  • Dawn White
  • M. A. Matteson Jr.
  • Paul Kelley

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Castings
  • Computational Science
  • Control Systems
  • Fuzzy Logic
  • Fuzzy Sets
  • Logic
  • Materials
  • Materials Engineering
  • Mathematical Models
  • Mathematics
  • Optical Detectors
  • Roughness
  • Set Theory
  • Ships
  • Spray Forming
  • Surface Properties
  • Surface Roughness

Readers

  • Image Processing and Computer Vision.
  • Internal Combustion Engine (ICE) Technology.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Directed Energy