首页> 外文会议>International Symposium on Structural Engineering for Young Experts;ISSEYE-10 >DATA-FUSION DAMAGE IDENTIFICATION METHOD BASED ON WAVELET PACKET DECOMPOSITION AND WEIGHTED-AVERAGE
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DATA-FUSION DAMAGE IDENTIFICATION METHOD BASED ON WAVELET PACKET DECOMPOSITION AND WEIGHTED-AVERAGE

机译:基于小波包分解和加权平均的数据融合损伤识别方法

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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.
机译:为了充分利用多资源的冗余和噪声数据,提高结构损伤的识别精度。提出了一种充分利用小波包的时频特性和数据融合的损伤识别新方法。在该方法中,首先分解响应信号,以通过小波包提取特征参数。然后采用不同的特征向量通过欧几里得距离来识别结构破坏模式。最后,采用加权平均来融合不同的识别结果。提出了7层钢结构的6种损伤模式以验证该方法。结果表明,该方法可以大大提高识别的准确性。

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