Structural damage identification using multifunctional Bragg grating sensors: II. Damage detection results and analysis

D. Betz, W. Staszewski, G.J. Thursby, B. Culshaw

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)


Structural health monitoring has become a respected and established discipline in engineering. Health monitoring involves the development of autonomous systems for continuous monitoring, inspection and damage detection of structures with minimum involvement of labour. The ultimate goal of structural health monitoring is to increase reliability, improve safety, enable light-weight design and reduce maintenance costs for all kinds of structures. The identification of structural damage is therefore a key issue in structural health monitoring. The scope of this paper is to present the results of testing a system for the identification of structural damage based on fibre Bragg grating sensors. The basic idea is to use fibre Bragg gratings as acoustic receivers of ultrasonic Lamb waves. The layout of such a damage identification system is introduced and its theoretical limits are studied numerically and experimentally. The set-up for damage identification experiments is described and the results of initial experiments introducing damage detection based on the analysis of Lamb wave signals are presented. The results for the Bragg grating sensors are then compared to the results of established technology for Lamb wave detection using piezoceramic transducers.
Original languageEnglish
Pages (from-to)1313-1322
Number of pages9
JournalSmart Materials and Structures
Issue number5
Publication statusPublished - 2006


  • structural health monitoring
  • autonomous systems
  • continuous monitoring
  • damage detection
  • safety
  • maintenance costs
  • fibre bragg grating sensors
  • lamb wave detection
  • piezoceramic transducers


Dive into the research topics of 'Structural damage identification using multifunctional Bragg grating sensors: II. Damage detection results and analysis'. Together they form a unique fingerprint.

Cite this