Identifying undamaged-beam status based on singular spectrum analysis and wavelet neural networks - Nguyen, Dung Sy; Nguyen, Hung Quoc; Ngo, Nhi Kieu (Journal of Computer Science and Cybernetics, 2016)
<span style="line-height: 115%; font-family: "Calibri","sans-serif"; font-size: 11pt; mso-ansi-language: EN-US; mso-bidi-font-family: ’Times New Roman’; mso-fareast-font-family: Calibri; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-US">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.