7 September 2006 Comparing surface particle coverage predictions with image analysis measurements
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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.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chien W. Chang, 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); doi: 10.1117/12.677326; https://doi.org/10.1117/12.677326


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