An integrated approach for structural damage identification using wavelet neuro-fuzzy model

被引：22

作者：

Zhu, Futao ^{[1
]}

Deng, Zhongmin ^{[1
]}

Zhang, Junfeng ^{[2
]}

机构：

[1] Beijing Univ Aeronaut & Astronaut, Sch Astronaut, Beijing 100191, Peoples R China

[2] Chinese Acad Sci, Inst Mech, Beijing 100080, Peoples R China

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2013年 / 40卷 / 18期

关键词：

Signal processing approach; Structural damage identification; Wavelet real-time filtering algorithm; Adaptive Neuro-Fuzzy Inference System; Interval modeling technique; UNCERTAINTY QUANTIFICATION; ANFIS; SYSTEM; ENSEMBLES; DIAGNOSIS; ANN;

D O I：

10.1016/j.eswa.2013.06.078

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：7415 / 7427

页数：13

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