Smart Structures and Systems

  • 제20권4호
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  • Pages.427-440
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  • 2017
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
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Damage detection in plate structures using frequency response function and 2D-PCA

  • Khoshnoudian, Faramarz (Faculty of Civil Engineering, Amirkabir University of Technology (Tehran Polytechnic)) ;
  • Bokaeian, Vahid (Faculty of Civil Engineering, Amirkabir University of Technology (Tehran Polytechnic))
  • 투고 : 2016.12.21
  • 심사 : 2017.08.22
  • 발행 : 2017.10.25
⟨ 이전 논문 다음 논문 ⟩

초록

One of the suitable structural damage detection methods using vibrational characteristics are damage-index-based methods. In this study, a damage index for identifying damages in plate structures using frequency response function (FRF) data has been provided. One of the significant challenges of identifying the damages in plate structures is high number of degrees of freedom resulting in decreased damage identifying accuracy. On the other hand, FRF data are of high volume and this dramatically decreases the computing speed and increases the memory necessary to store the data, which makes the use of this method difficult. In this study, FRF data are compressed using two-dimensional principal component analysis (2D-PCA), and then converted into damage index vectors. The damage indices, each of which represents a specific condition of intact or damaged structures are stored in a database. After computing damage index of structure with unknown damage and using algorithm of lookup tables, the structural damage including the severity and location of the damage will be identified. In this study, damage detection accuracy using the proposed damage index in square-shaped structural plates with dimensions of 3, 7 and 10 meters and with boundary conditions of four simply supported edges (4S), three clamped edges (3C), and four clamped edges (4C) under various single and multiple-element damage scenarios have been studied. Furthermore, in order to model uncertainties of measurement, insensitivity of this method to noises in the data measured by applying values of 5, 10, 15 and 20 percent of normal Gaussian noise to FRF values is discussed.

키워드

참고문헌

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피인용 문헌

  1. Structural damage detection in plates using a deep neural network-couple sparse coding classification ensemble method vol.27, pp.3, 2017, https://doi.org/10.1177/1077546320929156