Cited by 22Structural Health Monitoring TechniquesBladed Disk Vibration DynamicsMachine Fault Diagnosis Techniques

Fractal dimension based damage identification incorporating multi-task sparse Bayesian learning

Huang, Yong, Li, Hui, Wu, Stephen, Yang, Yongchao·2018·Smart Materials and Structures

Abstract

Abstract Sensitivity to damage and robustness to noise are critical requirements for the effectiveness of structural damage detection. In this study, a two-stage damage identification method based on the fractal dimension analysis and multi-task Bayesian learning is presented. The Higuchi’s fractal dimension (HFD) based damage index is first proposed, directly examining the time-frequency characteristic of local free vibration data of structures based on the irregularity sensitivity and noise robustness analysis of HFD. Katz’s fractal dimension is then presented to analyze the abrupt irregularity change of the spatial curve of the displacement mode shape along the structure. At the second stage, the multi-task sparse Bayesian learning technique is employed to infer the final damage localization vector, which borrow the dependent strength of the two fractal dimension based damage indication information and also incorporate the prior knowledge that structural damage occurs at a limited number of locations in a structure in the absence of its collapse. To validate the capability of the proposed method, a steel beam and a bridge, named Yonghe Bridge, are analyzed as illustrative examples. The damage identification results demonstrate that the proposed method is capable of localizing single and multiple damages regardless of its severity, and show superior robustness under heavy noise as well.

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Crossref · 10.1088/1361-665x/aac248

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Authors
Huang, Y., Li, H., Wu, S., & Yang, Y.
Affiliations
  • Harbin Institute of Technology (CN)
  • The Institute of Statistical Mathematics (JP)
  • Los Alamos National Laboratory (US)
Corresponding author
Huang, Yong
Venue
Smart Materials and Structures
Published
2018-06-01
Volume
27
Issue
7
Pages
075020
ISSN
  • 0964-1726 (ISSN-L)
  • 1361-665X
OpenAlex
W2802438791
Cited by
22
References
35
Citations by year
2026: 1 · 2025: 1 · 2024: 3 · 2023: 2 · 2022: 3 · 2021: 1 · 2020: 8 · 2019: 1 · 2018: 2
FWCI
2.70
Type
journal article
Language
en
Open access
closed
Locations
Smart Materials and Structures (publishedVersion)
Funders
National Natural Science Foundation of China (51308161)
Topics
  • Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
  • Physical Sciences › Engineering › Civil and Structural Engineering › Bladed Disk Vibration Dynamics
  • Physical Sciences › Engineering › Control and Systems Engineering › Machine Fault Diagnosis Techniques
Keywords
structural damage detection, damage localization, fractal dimension, Higuchi's fractal dimension, sparse Bayesian learning, multi-task learning, free vibration, noise robustness, steel beams, bridges

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