DATA-FUSION DAMAGE IDENTIFICATION METHOD BASED ON WAVELET PACKET DECOMPOSITION AND WEIGHTED-AVERAGE

In order to make full use of the redundant and noise data from the multi-resources, enhance the identification accuracy of structural damage. A new damage identification method is proposed which is making full use of good time-frequency characteristic of the wavelet packet and data fusion. In this method, the response signal is first decomposed so as to extract feature parameters by wavelet packet. Then different feature vectors are employed to identify the structural damage patterns by Euclidean distance. Finally, weighted-average is employed to fuze the different identification results. 6 damage patterns of a 7-story steel structure are presented to validate this method. The result shows that this proposed method can enhance the identification accuracy greatly.