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dc.contributor.authorHirst, E.
dc.contributor.authorKaye, Paul H.
dc.contributor.authorWang, Z.
dc.date.accessioned2008-04-07T19:50:51Z
dc.date.available2008-04-07T19:50:51Z
dc.date.issued1997
dc.identifier.citationHirst , E , Kaye , P H & Wang , Z 1997 , ' A neural network based spatial light scattering instrument for hazardous airborne fiber detection ' , Appl. Opt , vol. 36 , no. 24 , pp. 6149-6156 .
dc.identifier.issn0003-6935
dc.identifier.otherPURE: 163458
dc.identifier.otherPURE UUID: c67eabf1-9066-4952-b5bb-e209afa0751a
dc.identifier.otherdspace: 2299/1875
dc.identifier.otherScopus: 0001042508
dc.identifier.urihttp://hdl.handle.net/2299/1875
dc.descriptionThis paper was published in Applied Optics and is made available as an electronic reprint with the permission of OSA. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. Copyright OSA (www.osa.org/pubs/osajournals.org)
dc.description.abstractA 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 using a dedicated multi-element photodiode detector array. These data are subsequently processed using an artificial neural network which has previously been trained to recognise those features or patterns within the light scattering distribution which 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 upon 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 per second within a sample volume flow-rate of 1 litre per minute 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.en
dc.language.isoeng
dc.relation.ispartofAppl. Opt
dc.rightsOpen
dc.titleA neural network based spatial light scattering instrument for hazardous airborne fiber detectionen
dc.contributor.institutionSchool of Physics, Astronomy and Mathematics
dc.contributor.institutionScience & Technology Research Institute
dc.contributor.institutionCentre for Atmospheric and Climate Physics Research
dc.contributor.institutionParticle Instrumentation
dc.description.statusPeer reviewed
dc.relation.schoolSchool of Physics, Astronomy and Mathematics
dcterms.dateAccepted1997
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeOpen


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