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Author:

Yan, Wei-Ming (Yan, Wei-Ming.) (Scholars:闫维明) | Gu, Da-Peng (Gu, Da-Peng.) | Chen, Yan-Jiang (Chen, Yan-Jiang.) (Scholars:陈彦江) | Yang, Xiao-Sen (Yang, Xiao-Sen.)

Indexed by:

EI Scopus PKU CSCD

Abstract:

A damage detection method using BP neural network based on a novel damage index and the correlation characteristic of acceleration response was proposed, and was evaluated through FE simulations and test verifications. On the basis of achievements in existence, the feasibility of taking correlation characteristic as a damage index was validated theoretically. The damage detection for a simply-supported beam using the proposed method was simulated. The results showed that the trained BP neural network can correctly detect the location and level of damages in both single damage case and multi-damage case. A model test of a reinforced concrete simply-supported beam was performed to verify the validity and efficiency of the damage detection method.

Keyword:

Damage detection Concrete beams and girders Structural analysis Neural networks Reinforced concrete

Author Community:

  • [ 1 ] [Yan, Wei-Ming]Beijing Key Laboratory of Earthquake Engineering and Structural Retrofit, Beijing University of Technology, Beijing 100024, China
  • [ 2 ] [Gu, Da-Peng]Beijing Key Laboratory of Earthquake Engineering and Structural Retrofit, Beijing University of Technology, Beijing 100024, China
  • [ 3 ] [Chen, Yan-Jiang]Beijing Key Laboratory of Earthquake Engineering and Structural Retrofit, Beijing University of Technology, Beijing 100024, China
  • [ 4 ] [Yang, Xiao-Sen]Gansu Provincial Communications Planning Survey and Designing Institute CO., LTD, Lanzhou 730030, China

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Source :

Journal of Vibration and Shock

ISSN: 1000-3835

Year: 2013

Issue: 14

Volume: 32

Page: 82-86,92

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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