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Automatic error recognition apparatus

  • US 5,903,663 A
  • Filed: 02/15/1996
  • Issued: 05/11/1999
  • Est. Priority Date: 02/15/1995
  • Status: Expired due to Term
First Claim
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1. An automatic error recognition apparatus for automatically detecting and evaluating cracks in unitary objects during in-process testing by image recognition, the unitary objects being coated with a magnetic powder capable of fluorescence or with black powder which accumulates in any unitary cracks of the objects, the system comprising:

  • a three-dimensional testing apparatus including image recording means for obtaining images of selected segments of a surface on at least two sides of the unitary objects,ultraviolet lamps for illuminating the unitary objects in conjunction with the recordation of the images by said image recording means such that in the images, any magnetic power or black powder accumulated in cracks in the unitary objects contrasts with the surfaces of the unitary objects,a robot for transferring the unitary objects into and from said testing apparatus such that when the unitary objects are in said testing apparatus, said robot holds the unitary objects in precise, preselected positions relative to said image recording means to enable said image recording means to obtain images of the selected surface segments on said at least two sides of the unitary objects, andimage processing means coupled to said image recording means for receiving the images of the selected surface segments on said at least two sides of the unitary objects from said image recording means, said image processing means comprising a computer structured and arranged to evaluate the images of the selected surface segments for the presence of cracks in the selected surface segments to thereby detect any cracks in the selected surface segments, said image processing means being coupled to said robot to control actions of said robot with respect to the transfer of the unitary objects from said testing apparatus based on the evaluation of the images of the selected surface segments by said image processing means.

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