Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (72)
  • Open Access

    ARTICLE

    Estimation of Deformed Shapes of Beam Structures using 3D Coordinate Information from Terrestrial Laser Scanning

    H.M. Lee1, H.S. Park1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.29, No.1, pp. 29-44, 2008, DOI:10.3970/cmes.2008.029.029

    Abstract This paper presents a computational model to estimate deformed shapes of beam structures using 3D coordinate information from terrestrial laser scanning (TLS). The model is composed of five components: 1) formulation of polynomial shape function, 2) application of boundary condition, 3) inducement of compatibility condition, 4) application of the least square method and 5) evaluation of error vector and determination of reasonable polynomial shape function. In the proposed model, the optimal degree of polynomial function is selected based on the complexity of beam structures, instead of using a specific degree of polynomial function. The chosen polynomial function for estimation is… More >

  • Open Access

    ARTICLE

    Research on the Signal Reconstruction of the Phased Array Structural Health Monitoring Based Using the Basis Pursuit Algorithm

    Yajie Sun1,2,*, Yanqing Yuan2, Qi Wang2, Lihua Wang3, Enlu Li2, Li Qiao4

    CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 409-420, 2019, DOI:10.32604/cmc.2019.03642

    Abstract The signal processing problem has become increasingly complex and demand high acquisition system, this paper proposes a new method to reconstruct the structure phased array structural health monitoring signal. The method is derived from the compressive sensing theory and the signal is reconstructed by using the basis pursuit algorithm to process the ultrasonic phased array signals. According to the principles of the compressive sensing and signal processing method, non-sparse ultrasonic signals are converted to sparse signals by using sparse transform. The sparse coefficients are obtained by sparse decomposition of the original signal, and then the observation matrix is constructed according… More >

Displaying 71-80 on page 8 of 72. Per Page