Stochastic DLV method for steel truss structures: Simulation and experiment

Yonghui An, Jinping Ou, Jian Li, B. F. Spencer

Research output: Contribution to journalArticlepeer-review


The stochastic damage locating vector (SDLV) method has been studied extensively in recent years because of its potential to determine the location of damage in structures without the need for measuring the input excitation. The SDLV method has been shown to be a particularly useful tool for damage localization in steel truss bridges through numerical simulation and experimental validation. However, several issues still need clarification. For example, two methods have been suggested for determining the observation matrix C identified for the structural system; yet little guidance has been provided regarding the conditions under which the respective formulations should be used. Additionally, the specific layout of the sensors to achieve effective performance with the SDLV method and the associated relationship to the specific type of truss structure have yet to be explored. Moreover, how the location of truss members influences the damage localization results should be studied. In this paper, these three issues are first investigated through numerical simulation and subsequently the main results are validated experimentally. The results of this paper provide guidance on the effective use of the SDLV method.

Original languageEnglish (US)
Pages (from-to)105-128
Number of pages24
JournalSmart Structures and Systems
Issue number2
StatePublished - Aug 2014


  • Damage detection
  • Damage localization
  • Sensor layout
  • Steel-truss bridge
  • Stochastic damage locating vector (SDLV) method
  • Structural health monitoring

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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