Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification

被引:59
作者
Hakim, S. J. S. [1 ]
Razak, H. Abdul [1 ]
机构
[1] Univ Malaya, Dept Civil Engn, StrucHMRS Grp, Kuala Lumpur 50603, Malaysia
关键词
adaptive neuro fuzzy interface system (ANFIS); artificial neural networks (ANNs); backpropagation (BP); damage identification; experimental modal analysis; FAULT-DIAGNOSIS; PREDICTION; STRENGTH; BEAMS;
D O I
10.12989/sem.2013.45.6.779
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (ANNs) techniques are developed and applied to identify damage in a model steel girder bridge using dynamic parameters. The required data in the form of natural frequencies are obtained from experimental modal analysis. A comparative study is made using the ANNs and ANFIS techniques and results showed that both ANFIS and ANN present good predictions. However the proposed ANFIS architecture using hybrid learning algorithm was found to perform better than the multilayer feedforward ANN which learns using the backpropagation algorithm. This paper also highlights the concept of ANNs and ANFIS followed by the detail presentation of the experimental modal analysis for natural frequencies extraction.
引用
收藏
页码:779 / 802
页数:24
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