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Author:

Yu, Mengyao (Yu, Mengyao.) | Fu, Sheng (Fu, Sheng.) | Gao, Yinbo (Gao, Yinbo.) | Zheng, Hao (Zheng, Hao.) | Xu, Yonggang (Xu, Yonggang.)

Indexed by:

EI Scopus

Abstract:

A simple method was developed to detect damage based on a discrete mathematical model for fan blades using changes in natural frequencies combined with a fluid-structure analysis. In addition, a numerical approach was developed for the fluid-structure analysis. The results of numerical simulation provided the natural frequency data for each mode under different locations and sizes of a single crack in a blade. A fault database was built using Matlab. The damage of a blade was detected using the changes in natural frequencies. This study will assist in investigating the effect of a crack on a structure from different perspectives; the simulation results show the effectiveness of this approach. © 2018 Mengyao Yu et al.

Keyword:

Crack detection Fluid structure interaction Natural frequencies MATLAB Damage detection

Author Community:

  • [ 1 ] [Yu, Mengyao]Beijing Precision Metrology Laboratory, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Fu, Sheng]Beijing Precision Metrology Laboratory, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Gao, Yinbo]Beijing Precision Metrology Laboratory, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Zheng, Hao]Ennovation System Control Co., Ltd., Beijing; 101111, China
  • [ 5 ] [Xu, Yonggang]Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing; 100022, China

Reprint Author's Address:

  • [yu, mengyao]beijing precision metrology laboratory, beijing university of technology, beijing; 100124, china

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Related Keywords:

Source :

International Journal of Rotating Machinery

ISSN: 1023-621X

Year: 2018

Volume: 2018

ESI Discipline: ENGINEERING;

ESI HC Threshold:156

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 18

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 14

Online/Total:1007/10574162
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