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Entropy method for structural health monitoring based on statistical cause and effect analysis of acoustic emission and vibration signals
Citation
Tao, K and Zheng, W and Jiang, D, Entropy method for structural health monitoring based on statistical cause and effect analysis of acoustic emission and vibration signals, IEEE Access, 7 pp. 172515-172525. ISSN 2169-3536 (2019) [Refereed Article]
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Copyright Statement
Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/
DOI: doi:10.1109/ACCESS.2019.2956289
Abstract
Acoustic emission (AE) and vibration signal are significant criteria of damage identification
in structural health monitoring (SHM) engineering. Multi-disciplinary knowledge and synergistic parameter
effects are technical challenges for damage assessment modelling. This study proposes a structural damage
cause-and-effect analysis method based on parameter information entropy. Monitoring data is used to form
a time-domain feature wave (TFW). The structural strength degradation factor (DF) would be used to define
structural damage information entropy (SDIE) vector. The structural damage cause and effect model is
developed in a probability sense. A fatigue index is adopted for damage assessment, and a causal strength
index is proposed to locate the most likely damage cause. A sandstone-truss structure experiment was
conducted to show that the proposed method is effective for damage evaluation and the experimental results
provide strong support. This is a statistical damage identification method based on causal logic uncertainty,
meaning a complicated mechanics calculation can be avoided.
Item Details
Item Type: | Refereed Article |
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Keywords: | structural health monitoring, acoustic emission, cause-and-effect analysis, parameter information entropy |
Research Division: | Engineering |
Research Group: | Communications engineering |
Research Field: | Signal processing |
Objective Division: | Construction |
Objective Group: | Building management and services |
Objective Field: | Civil building management and services |
UTAS Author: | Tao, K ( Kai Tao) |
UTAS Author: | Jiang, D (Dr Danchi Jiang) |
ID Code: | 136511 |
Year Published: | 2019 |
Web of Science® Times Cited: | 6 |
Deposited By: | Engineering |
Deposited On: | 2020-01-03 |
Last Modified: | 2020-05-27 |
Downloads: | 34 View Download Statistics |
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