Structural Multi-Damage Pattern Recognition Based on Data Fusion and Energy-Damage

JIAO Li;LI Hong-nan;ZHANG hai;YI Ting-hua

Journal of Vibration and Shock ›› 2010, Vol. 29 ›› Issue (8) : 120-123.

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PDF(3068 KB)
Journal of Vibration and Shock ›› 2010, Vol. 29 ›› Issue (8) : 120-123.
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Structural Multi-Damage Pattern Recognition Based on Data Fusion and Energy-Damage

  • JIAO Li1,2;LI Hong-nan2;ZHANG hai1,2;YI Ting-hua2
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Abstract

A structural multi-damage identification method is presented based on consensus data fusion, eigenvalue extraction by energy-damage and the powerful pattern recognition function of ART2. The method can make full use of more structural status information in different site and recognize structural damage better. The traditional consensus data fusion algorithm is improved. The improved algorithm can overcomes the shortcoming of the traditional consensus algorithm with two sensors, which has different confidence distance for different measuring precision. And the supporting matrix is fuzzified, which can avoid the subjective error in determining the threshold value. Eigenvector of multi-sensor measured data after fusion are constructed using eigenvalue extraction technology of energy-damage. ART2 network is adopted as the pattern recognition to identify structural multi-damage. The numerical simulation results of a five-layer frame structure show that this method can identify structural multi-damage and it is more robust, stable and adaptive.

Key words

data fusion / consensus algorithm / feature extraction / pattern recognition

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JIAO Li;LI Hong-nan;ZHANG hai;YI Ting-hua. Structural Multi-Damage Pattern Recognition Based on Data Fusion and Energy-Damage[J]. Journal of Vibration and Shock, 2010, 29(8): 120-123
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