Paper
20 October 1975 Quality Control By Diffraction Pattern Analysis
Donald C. Mead, Harvey L. Kasdan, Thomas J. Middleton
Author Affiliations +
Proceedings Volume 0060, Solving Quality Control and Reliability Problems with Optics; (1975) https://doi.org/10.1117/12.954387
Event: Solving Quality Control and Reliability Problems with Optics, 1975, San Diego, United States
Abstract
Diffraction and scattering allow subtle defects to be detected at the high rates required for industrial quality control applications. Flaw detection in textile, transparent plastic, and steel webs has been demonstrated. Similar techniques may also be applied to many non-web problems such as walnut meat inspection, blade sharpness, wire diameter, and small part measurement. Several of these systems are currently under development and will soon take their place on the factory floor. In each of these cases, the diffraction pattern provides all the information necessary to determine product quality so that relatively few samples of the diffraction intensity pattern may be analyzed at high speed to detect the defect. Thus, diffraction pattern analysis offers a significant advantage over video scanning systems (even those based on a laser scanner) by minimizing the amount of data presented to the system for decision making. In most applications, video systems can simply not keep up with the rates required for on-line inspection. On the other hand diffraction systems generally illuminate a relatively large area and are able to operate at speeds required for on-line inspection.
© (1975) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Donald C. Mead, Harvey L. Kasdan, and Thomas J. Middleton "Quality Control By Diffraction Pattern Analysis", Proc. SPIE 0060, Solving Quality Control and Reliability Problems with Optics, (20 October 1975); https://doi.org/10.1117/12.954387
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Cited by 3 scholarly publications.
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KEYWORDS
Inspection

Diffraction

Defect detection

Sensors

Video

Pattern recognition

Scanners

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