Identifying undamaged-beam status based on singular spectrum analysis and wavelet neural networks


  • Dung Sy Nguyen Corresponding Author
  • Hung Quoc Nguyen Industrial University of Ho Chi Minh City
  • Nhi Kieu Ngo Ho Chi Minh City University of Technology



Singular spectrum analysis, frequency-based filter, wavelet neural networks, identifying structure.


In this paper, the identifying undamaged-beam status  based on singular spectrum analysis (SSA) and wavelet neural networks (WNN)  is presented. First, a database is built from measured sets and SSA which  works as a frequency-based filter. A WNN model is then designed which consists of the wavelet frame building, wavelet structure designing and  establishing a solution for training the WNN. Surveys via an experimental  apparatus for estimating the method are carried out. In this work, a  beam-typed iron frame, Micro-Electro-Mechanical (MEM) sensors and a  vibration-signal processing and measuring system named LAM_BRIDGE are all  used.


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Author Biography

Dung Sy Nguyen, Corresponding Author


I am a Postdoctoral fellow at Division of Mechanical System Engineering, Incheon National University, Korea

8-Rm105, (Songdo-dong) 119 Academi-ro, Yeonsu-gu, Incheon, 406-772, Korea.


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How to Cite

D. S. Nguyen, H. Q. Nguyen, and N. K. Ngo, “Identifying undamaged-beam status based on singular spectrum analysis and wavelet neural networks”, JCC, vol. 31, no. 4, p. 341, Jan. 2016.