Intelligent prognostic technologies based on optical fiber sensors for railway systems

Hwa Yaw Tam, Kei Chun Cheng, Shun Yee Liu, Weng Hong Chung, Lok Hin Cho, Ho Yin Au, Kang Kuen Lee

Research output: Journal article publicationConference articleAcademic researchpeer-review


Due to growing passenger demand for reliable service and safety improvement, therailway industry has been pushing for condition-based maintenance of railway infrastructure androlling stocks. We proposed a novel approach based on optical fiber sensors, offering an integratedsystem that allows continue tracking of health degradation, and extrapolate temporal behavior ofhealth indicators for effective maintenance and fault detection of railway systems.

Original languageEnglish
Pages (from-to)78-79
Number of pages2
JournalProceedings of SPIE - The International Society for Optical Engineering
Publication statusPublished - 2017
Event5th Workshop on Specialty Optical Fibers and Their Applications, WSOF 2017 - Limassol, Cyprus
Duration: 11 Oct 201713 Oct 2017

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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