Simultaneous measurement of temperature and strain: An artificial neural network approach

C. C. Chan, Wei Jin, A. B. Rad, M. S. Demokan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

15 Citations (Scopus)


In this letter, we report the use of an artificial neural network approach for simultaneous recovery of information about strain and temperature from fiber optic sensors. Simulation results show that, for a particular sensor with large cross-sensitivity, temperature and strain measurement accuracy can be increased by 12 and 3 times, respectively, when compared with the matrix inversion method.
Original languageEnglish
Pages (from-to)854-856
Number of pages3
JournalIEEE Photonics Technology Letters
Issue number6
Publication statusPublished - 1 Jun 1998


  • Fiber optics
  • Neural networks
  • Strain measurement
  • Temperature measurement

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics
  • Physics and Astronomy (miscellaneous)

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