Presentation + Paper
12 April 2021 Predicting instrument detection capability of dispersed samples while moving
Author Affiliations +
Abstract
The detection of bulk materials is well-understood and many transduction methodologies exist. In contrast the detection of distributed or dispersed materials is still under study due the unique sequence of events under which this this occurs. For dispersed materials the problem is twofold, first you need to intercept or sample a location containing an analyte of interest and second you must be able to detect and identify that analyte. In addition, intercepting or sampling from sparsely contaminated areas is a more difficult problem as there is more background clutter due to less analyte available for interrogation and identification. Potential dispersed threats may include IED residues or disseminated materials dispersed in order contaminate an area with harmful chemicals. Using technologies such as Raman spectroscopy can provide real-time unique chemical-specific information to detect dispersed materials. However, understanding adequate sampling methods based on the instrument physical operation characteristics can help reduce false negatives and improve maneuverability through contested areas by bounding operational limitations. Since disseminated materials are deposited on a surfaces in a log-Normal fashion, the deposition pattern can be modeled and the potential ability to detect can be determined by understanding the probability of intercept of an analyte by the sampling method., i.e., for Raman the potential of a focused laser to illuminate an analyte containing location. The operating characteristics in question are the area of interrogation, repetition rate of the sampling method, and the speed at which the sampling is completed. In this paper, deposition patterns are modeled, and a CW Raman instrument is used to determine probability of intercept for several area-based concentrations, at different speeds, and with different interrogation areas. The data is analyzed based on both a predicted model and actual data. Determining and understanding these operating characteristics will aid in understanding of the necessary sampling, i.e., laser intercept, in order to provide desired confidence levels for detection.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Eric R. Languirand and Darren K. Emge "Predicting instrument detection capability of dispersed samples while moving", Proc. SPIE 11749, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XXII, 117490O (12 April 2021); https://doi.org/10.1117/12.2587179
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KEYWORDS
Data modeling

Raman spectroscopy

Chemical analysis

Improvised explosive devices

Instrument modeling

Solids

Spectroscopy

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