Mine Fire Source Discrimination Using Fire Sensors and Neural Network Analysis

Details

• Personal Author:
  Edwards, J. C. ; Friel, G. F. ; Franks, R. A. ; Lazzara, C. P. ; Opferman, J. J.
• Description:
  Fire experiments were conducted in the Safety Research Coal Mine (SRCM) at the National Institute for Occupational Safety and Health, Pittsburgh Research Laboratory, with coal, diesel-fuel, electrical-cable, conveyor-belt, and metal-cutting fire sources to determine the response of fire sensors to products-of-combustion (POC). Metal oxide semiconductor (MOS) and smoke fire sensors demonstrated an earlier fire detection capability than a CO sensor. This capability was of particular significance for a conveyor-belt fire in which the optical visibility was reduced to 1.52 m with an increase in CO of less than 2 ppm at a distance of 148 m from the fire. Application of a neural-network program to the sensor responses from each type of fire source resulted in correct classifications of coal, diesel-fuel, cable, belt, and metal-cutting combustion with a mean of 96% of the test data correctly classified.
• Subjects:
  NIOSH
• Document Type:
  Text
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• NIOSHTIC Number:
  nn:20020920
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:d56b0e447ae919c00adeba7fcd2afa6a2335e6f10588e7158e83aa297a38e406b249f86c742419309ff55f8f433271c979bff3de9d305b47090b9dd3098827dd
• Download URL:
  https://stacks.cdc.gov/view/cdc/9789/cdc_9789_DS1.pdf
• File Type:
  [PDF - 207.53 KB ]