Least-Squares Estimation with Unknown Excitations for Damage Identification of Structures

System identification and damage detection for structural health monitoring of civil infrastructures have received considerable attention of late. Time domain analysis methodologies based on measured vibration data, such as least-squares estimation and the extended Kalman filter, were studied and shown to be useful. The traditional least-squares estimation method requires that all the external excitation data (input data) be available, which may not be the case for many structures. In this paper, a recursive least-squares estimation with unknown inputs (RLSE-UI) approach is proposed to identify the structural parameters, such as stiffness, damping, and other nonlinear parameters, as well as the unmeasured excitations. Analytical recursive solutions for the proposed RLSE-UI are derived and presented. This analytical recursive solution for RLSE-UI is not available in the prior literature. An adaptive tracking technique newly developed is implemented in the proposed approach to track the variations of structural parameters due to damages. Simulation results demonstrate the proposed approach is capable of identifying the structural parameters, their variations due to damages, and unknown excitations.

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  • Supplemental Notes:
    • Abstract reprinted with permission from ASCE
  • Authors:
    • Yang, Jann N
    • Pan, Shuwen
    • Lin, Silian
  • Publication Date: 2007-1


  • English

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  • Accession Number: 01045088
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Mar 1 2007 8:46PM