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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 36, Iss. 24 — Aug. 20, 1997
  • pp: 6149–6156

Neural-network-based spatial light-scattering instrument for hazardous airborne fiber detection

Paul Kaye, Edwin Hirst, and Zhenni Wang-Thomas  »View Author Affiliations


Applied Optics, Vol. 36, Issue 24, pp. 6149-6156 (1997)
http://dx.doi.org/10.1364/AO.36.006149


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Abstract

A laser light-scattering instrument has been designed to facilitate the real-time detection of potentially hazardous respirable fibers, such as asbestos, within an ambient environment. The instrument captures data relating to the spatial distribution of light scattered by individual particles in flow by use of a dedicated multielement photodiode detector array. These data are subsequently processed with an artificial neural network that has previously been trained to recognize those features or patterns within the light-scattering distribution that may be characteristic of the specific particle types being sought, such as, for example, crocidolite or chrysotile asbestos fibers. Each particle is thus classified into one of a limited set of classes based on its light-scattering properties, and from the accumulated data a particle concentration figure for each class may be produced and updated at regular intervals. Particle analysis rates in excess of 103/s within a sample volume flow rate of 1 l/min are achievable, offering the possibility of detecting fiber concentrations at the recommended maximum exposure limit of 0.1 fibers/ml within a sampling period of a few seconds.

© 1997 Optical Society of America

History
Original Manuscript: January 14, 1997
Revised Manuscript: April 28, 1997
Published: August 20, 1997

Citation
Paul Kaye, Edwin Hirst, and Zhenni Wang-Thomas, "Neural-network-based spatial light-scattering instrument for hazardous airborne fiber detection," Appl. Opt. 36, 6149-6156 (1997)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-36-24-6149

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