Comparing surface particle coverage predictions with image analysis measurements

Chien W. Chang

doi:10.1117/12.677326

7 September 2006 Comparing surface particle coverage predictions with image analysis measurements

Chien W. Chang

Proceedings Volume 6291, Optical Systems Degradation, Contamination, and Stray Light: Effects, Measurements, and Control II; 62910K (2006) https://doi.org/10.1117/12.677326
Event: SPIE Optics + Photonics, 2006, San Diego, California, United States

Abstract

This paper describes a numerical model developed recently using MATLAB^® for performing surface particle coverage calculations. The model uses a multi-bin particle size distribution model with incorporation of Barengoltz's areal density integration method and Raab's particle shape factor, a similar approach employed previously by Ma, Fong and Lee at Lockheed Martin Space Systems Company (Sunnyvale). The developed model is a versatile and quick turnaround tool and can easily account for variable particle size bins, variable shape factors or aspect ratios for various size bins, and variable slopes (w.r.t. the IEST-STD-CC1246 slope) for different size bins. Model predictions compare well with image analysis measurements of particle fallout data from various spacecraft cleanrooms and test environments. Moreover, this study recommends using a standard equation to correlate particle area coverage with IEST-STD-CC1246 levels (particles modeled as a cylinder with hemispherical ends) and applying a wide range of conversion factors for accurately calculating particle area coverage for variable slopes for different particle size bins.

Citation Download Citation

Chien W. Chang "Comparing surface particle coverage predictions with image analysis measurements", Proc. SPIE 6291, Optical Systems Degradation, Contamination, and Stray Light: Effects, Measurements, and Control II, 62910K (7 September 2006); https://doi.org/10.1117/12.677326

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