An integrated approach for structural damage identification using wavelet neuro-fuzzy model |
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Authors: | Futao Zhu Zhongmin Deng Junfeng Zhang |
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Affiliation: | 1. School of Astronautics, Beijing University of Aeronautics and Astronautics, 37 XueYuan Road, Haidian District, Beijing 100191, China;2. Institute of Mechanics, Chinese Academy of Sciences, 100080 Beijing, China |
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Abstract: | Structural damage can be identified by processing structural vibration response signals and excitation data, and thus the suitability of signal processing methods is essential to structural damage identification. To explore an intelligent signal processing method for structural damage identification, the paper integrated wavelet real-time filtering algorithm, Adaptive Neruo-Fuzzy Inference System (ANFIS) and interval modeling technique to process structural response signals and excitation data. With Wavelet Transform (WT) algorithm filtering random noise, ANFIS was found to model the structural behavior properly and interval modeling technique to quantify damage index accurately. The rapid identifications of several unknown damages and small damages indicate the efficiency of this integrated method. The comparison of these results and some other signal processing methods shows that, the proposed method can be used to identify both the time and the location when the structural damage occurs unexpectedly. |
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Keywords: | Signal processing approach Structural damage identification Wavelet real-time filtering algorithm Adaptive Neuro-Fuzzy Inference System Interval modeling technique |
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