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Title: Smoke detection

Various apparatus and methods for smoke detection are disclosed. In one embodiment, a method of training a classifier for a smoke detector comprises inputting sensor data from a plurality of tests into a processor. The sensor data is processed to generate derived signal data corresponding to the test data for respective tests. The derived signal data is assigned into categories comprising at least one fire group and at least one non-fire group. Linear discriminant analysis (LDA) training is performed by the processor. The derived signal data and the assigned categories for the derived signal data are inputs to the LDA training. The output of the LDA training is stored in a computer readable medium, such as in a smoke detector that uses LDA to determine, based on the training, whether present conditions indicate the existence of a fire.
Inventors:
; ;
Issue Date:
OSTI Identifier:
1320884
Assignee:
UT-Battelle, LLC (Oak Ridge, TN) ORNL
Patent Number(s):
9,437,092
Application Number:
14/859,631
Contract Number:
AC05-00OR22725
Resource Relation:
Patent File Date: 2015 Sep 21
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
47 OTHER INSTRUMENTATION; 99 GENERAL AND MISCELLANEOUS

Other works cited in this record:

Advanced fire detection algorithms using data from the home smoke detector project
journal, February 2005

Development Of A Fire Detection System Using Ft-ir Spectroscopy And Artificial Neural Networks
journal, January 2000

Advanced fire detection using multi-signature alarm algorithms
journal, June 2002
  • Gottuk, Daniel T.; Peatross, Michelle J.; Roby, Richard J.
  • Fire Safety Journal, Vol. 37, Issue 4, p. 381-394
  • DOI: 10.1016/S0379-7112(01)00057-1

Multi-criteria fire detection systems using a probabilistic neural network
journal, October 2000
  • Rose-Pehrsson, Susan L.; Shaffer, Ronald E.; Hart, Sean J.
  • Sensors and Actuators B: Chemical, Vol. 69, Issue 3, p. 325-335
  • DOI: 10.1016/S0925-4005(00)00481-0

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