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author:

Jiang, Shao-Fei (Jiang, Shao-Fei.) [1] (Scholars:姜绍飞) | Fu, Chun (Fu, Chun.) [2] | Wu, Zhao-Qi (Wu, Zhao-Qi.) [3]

Indexed by:

CPCI-S EI Scopus

Abstract:

To extract effectively features and improve damage identification precision, this study proposed an intelligent data-fusion model by integrating fractal theory, probabilistic neural network (PNN) and data fusion. A two-span concrete-filled steel tubular arch bridge in service was used to validate the intelligent model by identifying both single- and multi-damage patterns. The results show that the intelligent model proposed can not only reliably identify damage with different noise levels, but also have an excellent anti-noise capability and robustness.

Keyword:

correlation fractal dimension damage detection data fusion probabilistic neural network

Community:

  • [ 1 ] [Jiang, Shao-Fei]Fuzhou Univ, Coll Civil Engn, Fuzhou 350108, Peoples R China
  • [ 2 ] [Fu, Chun]Fuzhou Univ, Coll Civil Engn, Fuzhou 350108, Peoples R China
  • [ 3 ] [Wu, Zhao-Qi]Fuzhou Univ, Coll Civil Engn, Fuzhou 350108, Peoples R China

Reprint 's Address:

  • 姜绍飞

    [Jiang, Shao-Fei]Fuzhou Univ, Coll Civil Engn, Fuzhou 350108, Peoples R China

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Source :

SMART MATERIALS AND INTELLIGENT SYSTEMS, PTS 1 AND 2

ISSN: 1022-6680

Year: 2011

Volume: 143-144

Page: 1300-1304

Language: English

Cited Count:

WoS CC Cited Count: 2

SCOPUS Cited Count: 6

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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