A Formulation of a Stochastic Sampling Error Model and a Signal Detection Algorithm for the Aerodynamic Particle Size Analyser

Abstract

The determination of the distribution of airborne toxic particles as a function of the aerodynamic diameter provides important information as well as criteria for the definition of hazard as applied to levels of airborne contamination. This is because the aerodynamic particle size distribution embodies the information related to particle density, diameter, shape factor and slip correction that is critical for the characterization of particle motion in settling and impaction and it is these motions that are responsible for particle deposition in the respiratory tract and particle collection in aerosol sampling devices. For a given definition of hazard based on some parameter related to the aerodynamic size distribution, this paper develops a statistical sampling error model for the parameter that is based on the Poisson process. Given that an appropriate sampling program has been designed for the measurement of the size distribution-related parameter with the aerodynamic particle size analyzer, this paper proceeds to the derivation of an optimum detection algorithm for the detection of a signal aerosol sequence in a set of J aerosol samples with a common background. The detection algorithm is based on the generalized likelihood ratio test in which the received count associated with the aerosol sample is modeled as a Poisson distributed random variable.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1991
Accession Number
ADA238183

Entities

People

  • Eugene Yee

Organizations

  • Defence Research and Development Canada

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Airborne
  • Algorithms
  • Analyzers
  • Classification
  • Detection
  • Detectors
  • Distribution Functions
  • False Alarms
  • Hazards
  • Light Sources
  • Particle Size
  • Probability
  • Random Variables
  • Signal Detection
  • Statistical Sampling
  • Warning Systems

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aerosol Science/Aerosol Physics