The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 03, 1981

Filed:

Aug. 09, 1978
Applicant:
Inventors:

Nicholas Yaroshuk, White Oak, PA (US);

Miklos Sarkozi, Murrysville, PA (US);

Robert C Miller, Penn Hills, PA (US);

Paul G Kennedy, Monroeville, PA (US);

Assignee:

Westinghouse Electric Corp., Pittsburgh, PA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G01N / ;
U.S. Cl.
CPC ...
356431 ; 250563 ; 356237 ;
Abstract

This invention is a system of automatically classifying defects both for sorting defective products (metallic surfaces, especially tube surfaces) as to the reworking operation required for correcting the defect, and for classifying the defect as to the preceding manufacturing operation which is the most probable cause of that defect and sending a signal to that operation to provide for adjustments to minimize future defects. The system uses a source of electromagnetic radiation (typically a laser beam which is scanned across the surface) and at least two sensors (adjusted such that the radiation is reflected from a defect-free surface principally received by one of the sensors but that there is a measured amount of radiation in the other sensor). An average signal of the principal sensor is developed as a function of scan position. Threshold circuitry detects when the ratio of sensor signal to average signal varies by a predetermined amount. Special circuitry is used to detect the essentially simultaneous occurrence of at least two different preselected combinations of signal variations to identify the type of defect.


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