Paper
1 November 1992 Automated anomaly detection for orbiter high-temperature reusable surface insulation
Eric G. Cooper, Sharon M. Jones, Plesent W. Goode, Sixto L. Vazquez
Author Affiliations +
Proceedings Volume 1829, Cooperative Intelligent Robotics in Space III; (1992) https://doi.org/10.1117/12.131710
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States
Abstract
The description, analysis, and experimental results of a method for identifying possible defects on high temperature reusable surface insulation (HRSI) of the Orbiter thermal protection system (TPS) is presented. Currently, a visual postflight inspection of Orbiter TPS is conducted to detect and classify defects as part of the Orbiter maintenance flow. The objective of the method is to automate the detection of defects by identifying anomalies between preflight and postflight images of TPS components. The initial version is intended to detect and label gross (greater than 0.1 inches in the smallest dimension) anomalies on HRSI components for subsequent classification by a human inspector. The approach is a modified Golden Template technique where the preflight image of a tile serves as the template against which the postflight image of the tile is compared. Candidate anomalies are selected as a result of the comparison and processed to identify true anomalies. The processing methods are developed and discussed, and the results of testing on actual and simulated tile images are presented. Solutions to the problems of brightness and spatial normalization, timely execution, and minimization of false positives are also discussed.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Eric G. Cooper, Sharon M. Jones, Plesent W. Goode, and Sixto L. Vazquez "Automated anomaly detection for orbiter high-temperature reusable surface insulation", Proc. SPIE 1829, Cooperative Intelligent Robotics in Space III, (1 November 1992); https://doi.org/10.1117/12.131710
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Cited by 3 scholarly publications.
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KEYWORDS
Defect detection

Inspection

Optical inspection

Image processing

Visualization

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