Paper Title:
Structural Damage Identification Based on Hilbert-Huang Transform and Verification via Shaking Table Model Test
  Abstract

Damage occurs in components and joints while the structure is affected by strong ground motions. Dynamic characteristics of the structure will change with the deterioration of strength and stiffness. Analyzing and processing the vibration signals is one of the mainstream ways for structural health monitoring and damage identification. In this paper, Hilbert-Huang transform is adopted to identify structural damage. Time-varying instantaneous frequency and instantaneous energy is used to identify the damage evolution of the structure. And relative amplitude of Hilbert marginal spectrum is used to identify the damage location of the structure. Finally, the acceleration records at gauge points from the shaking table test of a 12-storey reinforced concrete frame model are processed. Evolution and location of the model damage are identified. Identification results agree well with experimental observation. This indicates that the proposed approach is capable to identify damage of the structure.

  Info
Periodical
Advanced Materials Research (Volumes 255-260)
Edited by
Jingying Zhao
Pages
4237-4241
DOI
10.4028/www.scientific.net/AMR.255-260.4237
Citation
J. P. Han, J. Qian, P. J. Zheng, "Structural Damage Identification Based on Hilbert-Huang Transform and Verification via Shaking Table Model Test", Advanced Materials Research, Vols. 255-260, pp. 4237-4241, 2011
Online since
May 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Wei Tang, Yu Yang Lian, Xi Chen, Zhi Yong Pei, Qi Wang
Chapter 4: Practice of Data Processing for Intelligent Systems
Abstract:Aiming at the mode mixing problem caused by interpolation point selection of conventional EMD (Empirical mode decomposition) method, a...
451
Authors: Zhi Jun Dai, Yu Fa Xu, Xiao Juan Mei, Qiang Qiang Su
Chapter 1: Applied Mechanics and Dynamics, Mechanical Engineering, Manufacturing
Abstract:The randomness of wind power and the nonstationarity of gearbox vibration signals greatly increased the difficulty of wind turbine gearbox...
195