Paper
15 January 2007 Measurement of low-absorption optics by thermal imaging
Alan F. Stewart, William Hughes
Author Affiliations +
Abstract
An infrared camera system has been used to measure absorption in optical coatings and substrates. Laser light is directed at the test sample and milliwatts of power are absorbed. The camera images the surface of the sample and provides a direct measurement of the 8-12 micron radiation emitted. By considering the effective emissivity of the sample and the ambient temperature, the surface temperature of the sample is obtained. Through the use of an equivalent "reference" sample which is not heated by the laser, background variations may be effectively eliminated. The application of standard calorimetric methods to infrared imaging as well as the availability of improved sensors such as the microbolometer array has led to our ability to resolve temperature excursions as low as 0.01°C with a S/N of 20 for typical samples. The IR imaging method has been used to evaluate many optical coatings and window materials for the Airborne Laser program. Because the method is noncontact, it has been used to directly measure absorption on large optical surfaces. In some instances, defects have been observed and mapped using this method. Variations in absorption which might be predicted from the coating design have been measured directly. The IR imaging technique thus offers great flexibility and sensitivity comparable to precision calorimetry.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alan F. Stewart and William Hughes "Measurement of low-absorption optics by thermal imaging", Proc. SPIE 6403, Laser-Induced Damage in Optical Materials: 2006, 64031H (15 January 2007); https://doi.org/10.1117/12.696277
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Absorption

Coating

Infrared imaging

Cameras

Thermography

Data modeling

Calibration

Back to Top