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| Data-fusion damage detection approach based on probabilistic neural network classifier |
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| DOI：10.7511/jslx20085132 |
| KeyWord:damage detection,data fusion,wavelet energy feature,feature extraction,probabilistic neural network |
| JIANG Shao-fei ZHANG Shuai |
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| Abstract: |
| In order to make full use of the redundant and complementary information and thus assess the structural health states from a large structural health monitoring system,the principle of data fusion was first introduced in this paper,then a 5-phase novel decision-level data fusion damage detection approach by integrating wavelet analysis,probabilistic neural network(PNN) and data fusion developed and implemented.Finally,two numerical examples validated the proposed method,the effect of measurement noise on identification accuracy was investigated as well.The result shows that the proposed method is feasible and effective for damage identification. |
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