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Smart Structures and Systems
  Volume 21, Number 1, January 2018 , pages 001-14

Application of couple sparse coding ensemble on structural damage detection
Milad Fallahian, Faramarz Khoshnoudian and Saeid Talaei

    A method is proposed to detect structural damages in the presence of damping using noisy data. This method uses Frequency Response Function (FRF) and Mode-Shapes as the input parameters for a system of Couple Sparse Coding (CSC) to study the healthy state of the structure. To obtain appropriate patterns of FRF for CSC training, Principal Component Analysis (PCA) technique is adopted to reduce the full-size FRF to overcome over-fitting and convergence problems in machine-learning training. To verify the proposed method, a numerical two-story frame structure is employed. A system of individual CSCs is trained with FRFs and mode-shapes, and then termed ensemble to detect the health condition of the structure. The results demonstrate that the proposed method is accurate in damage identification even in presence of up to 20% noisy data and 5% unconsidered damping ratio. Furthermore, it can be concluded that CSC ensemble is highly efficient to detect the location and the severity of damages in comparison to the individual CSC trained only with FRF data.
Key Words
    couple sparse coding; damage detection; frequency response function; principal component analysis; ensemble
Milad Fallahian and Faramarz Khoshnoudian: Faculty of Civil Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
Saeid Talaei: Young Researchers and Elite Club, Central Tehran Branch, Islamic Azad University, Tehran, Iran

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