Damage identification of structures with substructural flexibility

Yong Xia, Xiaoqing Zhou, Shun Weng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


Structural health monitoring systems rely on algorithms to detect potential changes in structural parameters that may be indicative of damage. For a large-scale structure, the local damage usually introduces slight change to the global modal data, which makes the local damage difficult to be detected. This paper proposes a new substructuring method for the damage detection of a structure. The global structure is divided into manageable substructures. The modal data measured on the global structure are disassembled for obtaining the independent substructural dynamic flexibility matrices, under the force and displacement compatibility constraints. Afterwards, the substructural flexibility matrix is decomposed into its eigenvalues and eigenvectors to be used as the indicators for damage detection. Since the substructuring method concerns the local area by treating it as an independent structure, the substructural eigenparameters are more sensitive to the local damage than the global eigenparameters. The proposed substructuring method is integrated with probability and statistical analysis upon a laboratory-tested portal frame structure.
Original languageEnglish
Title of host publicationProceedings of the 12th International Symposium on Structural Engineering, ISSE 2012
Number of pages8
Publication statusPublished - 1 Dec 2012
Event12th International Symposium on Structural Engineering, ISSE 2012 - Wuhan, China
Duration: 17 Nov 201219 Nov 2012


Conference12th International Symposium on Structural Engineering, ISSE 2012


  • Damage detection
  • Structural health monitoring
  • Substructure method

ASJC Scopus subject areas

  • Civil and Structural Engineering


Dive into the research topics of 'Damage identification of structures with substructural flexibility'. Together they form a unique fingerprint.

Cite this