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

Dung Sy Nguyen, Hung Quoc Nguyen, Nhi Kieu Ngo
Author affiliations

Authors

  • 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

DOI:

https://doi.org/10.15625/1813-9663/31/4/6417

Keywords:

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

Abstract

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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Published

15-01-2016

How to Cite

[1]
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.

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Section

Cybernetics