Structural Damage Identification Method Based on IMF Model Energy Feature and BP Neural Network

Author

Sun, Zhaowei ; Shi, Gang ; Liu, Xiaoping

Author_Institution

Sch. of Autom., Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2011

fDate

20-21 Aug. 2011

Firstpage

206

Lastpage

209

Abstract

This paper brings forward a structural damage identification method that integrates energy characteristics of intrinsic mode functions (IMFs) and BP neural networks. This method begins with decomposing acceleration response of structure into the IMFs by EMD and calculates the model energy feature of signal. The input vectors, which are got by combination of IMF model energy feature from the different test points, can be inputted into BP neural networks so that the neural networks can diagnose the fault. The concrete steps is given in this paper, and the feasibility and effectiveness of this method are tested via the simulation experiments.

Keywords

backpropagation; fault diagnosis; neural nets; structural engineering computing; BP neural network; acceleration response decomposing; empirical mode decomposition; energy characteristics; fault diagnosis; intrinsic mode function model energy feature; structural damage identification method; Adaptation models; Biological neural networks; Entropy; Finite element methods; Mathematical model; Neurons; BP neural network; IMF model energy feature; empirical mode decomposition (EMD); structural damage identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligence Science and Information Engineering (ISIE), 2011 International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4577-0960-9

Electronic_ISBN

978-0-7695-4480-9

Type

conf

DOI

10.1109/ISIE.2011.70

Filename

5997416