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  • Open Access

    ARTICLE

    Identification of Damage in Steel‒Concrete Composite Beams Based on Wavelet Analysis and Deep Learning

    Chengpeng Zhang, Junfeng Shi*, Caiping Huang

    Structural Durability & Health Monitoring, Vol.18, No.4, pp. 465-483, 2024, DOI:10.32604/sdhm.2024.048705 - 05 June 2024

    Abstract In this paper, an intelligent damage detection approach is proposed for steel-concrete composite beams based on deep learning and wavelet analysis. To demonstrate the feasibility of this approach, first, following the guidelines provided by relevant standards, steel-concrete composite beams are designed, and six different damage incidents are established. Second, a steel ball is used for free-fall excitation on the surface of the steel-concrete composite beams and a low-temperature-sensitive quasi-distributed long-gauge fiber Bragg grating (FBG) strain sensor is used to obtain the strain signals of the steel-concrete composite beams with different damage types. To reduce the… More >

  • Open Access

    ARTICLE

    Frequencies Prediction of Laminated Timber Plates Using ANN Approach

    Jianping Sun1, Jan Niederwestberg2,*, Fangchao Cheng1, Yinghei Chui2

    Journal of Renewable Materials, Vol.8, No.3, pp. 319-328, 2020, DOI:10.32604/jrm.2020.08696 - 01 March 2020

    Abstract Cross laminated timber (CLT) panels, which are used as load bearing plates and shear panels in timber structures, can serve as roofs, walls and floors. Since timber is construction material with relatively less stiffness, the design of such structures is often driven by serviceability criteria, such as deflection and vibration. Therefore, accurate vibration and elastic properties are vital for engineered CLT products. The objective of this research is to explore a method to determine the natural frequencies of orthotropic wood plates efficiently and fast. The method was developed based on vibration signal processing by wavelet More >

  • Open Access

    ARTICLE

    AdaBoosting Neural Network for Short-Term Wind Speed Forecasting Based on Seasonal Characteristics Analysis and Lag Space Estimation

    Haijian Shao1, 2, Xing Deng1, 2, *

    CMES-Computer Modeling in Engineering & Sciences, Vol.114, No.3, pp. 277-293, 2018, DOI:10.3970/cmes.2018.114.277

    Abstract High accurary in wind speed forcasting remains hard to achieve due to wind’s random distribution nature and its seasonal characteristics. Randomness, intermittent and nonstationary usually cause the portion problem of the wind speed forecasting. Seasonal characteristics of wind speed means that its feature distribution is inconsistent. This typically results that the persistence of excitation for modeling can not be guaranteed, and may severely reduce the possibilities of high precise forecasting model. In this paper, we proposed two effective solutions to solve the problems caused by the randomness and seasonal characteristics of the wind speed. (1)… More >

  • Open Access

    ARTICLE

    A Real-time Monitoring Technique for Local Plasticity in Metals Based on Lamb Waves and a Directional Actuator/Sensor Set

    Y. L. Liu1, N. Hu2, H. Xu3, H. Ning1, L. K. Wu1

    CMC-Computers, Materials & Continua, Vol.40, No.1, pp. 1-20, 2014, DOI:10.3970/cmc.2014.040.001

    Abstract A real-time monitoring technique for local plasticity using Lamb waves was developed. Tensile test of a thin aluminum plate with a circular hole where high stress concentration was induced was conducted to verify this technique. During the tensile test, a series of wave signals passing through the local plastic region were collected using a directional actuator/sensor set to monitor plasticity evolution. A pulse compression technique was used to process the wave signals. With the increase of tensile stress in the specimen, the amplitude changes of S0 and A0 modes were obtained and the difference of Lamb… More >

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