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Entropy method for structural health monitoring based on statistical cause and effect analysis of acoustic emission and vibration signals
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Abstract
Acoustic emission (AE) and vibration signal are significant criteria of damage identificationin structural health monitoring (SHM) engineering. Multi-disciplinary knowledge and synergistic parametereffects are technical challenges for damage assessment modelling. This study proposes a structural damagecause-and-effect analysis method based on parameter information entropy. Monitoring data is used to forma time-domain feature wave (TFW). The structural strength degradation factor (DF) would be used to definestructural damage information entropy (SDIE) vector. The structural damage cause and effect model isdeveloped in a probability sense. A fatigue index is adopted for damage assessment, and a causal strengthindex is proposed to locate the most likely damage cause. A sandstone-truss structure experiment wasconducted to show that the proposed method is effective for damage evaluation and the experimental resultsprovide strong support. This is a statistical damage identification method based on causal logic uncertainty,meaning a complicated mechanics calculation can be avoided.
Item Type: | Article |
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Authors/Creators: | Tao, K and Zheng, W and Jiang, D |
Keywords: | structural health monitoring, acoustic emission, cause-and-effect analysis, parameter information entropy |
Journal or Publication Title: | IEEE Access |
Publisher: | Institute of Electrical and Electronics Engineers |
ISSN: | 2169-3536 |
DOI / ID Number: | 10.1109/ACCESS.2019.2956289 |
Copyright Information: | Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/ |
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