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  • Open Access

    ARTICLE

    A Monitoring Method for Transmission Tower Foots Displacement Based on Wind-Induced Vibration Response

    Zhicheng Liu1, Long Zhao1,*, Guanru Wen1, Peng Yuan2, Qiu Jin1

    Structural Durability & Health Monitoring, Vol.17, No.6, pp. 541-555, 2023, DOI:10.32604/sdhm.2023.029760 - 17 November 2023

    Abstract The displacement of transmission tower feet can seriously affect the safe operation of the tower, and the accuracy of structural health monitoring methods is limited at the present stage. The application of deep learning method provides new ideas for structural health monitoring of towers, but the current amount of tower vibration fault data is restricted to provide adequate training data for Deep Learning (DL). In this paper, we propose a DT-DL based tower foot displacement monitoring method, which firstly simulates the wind-induced vibration response data of the tower under each fault condition by finite element… More > Graphic Abstract

    A Monitoring Method for Transmission Tower Foots Displacement Based on Wind-Induced Vibration Response

  • Open Access

    ARTICLE

    Integrated CWT-CNN for Epilepsy Detection Using Multiclass EEG Dataset

    Sidra Naseem1, Kashif Javed1, Muhammad Jawad Khan1, Saddaf Rubab2, Muhammad Attique Khan3, Yunyoung Nam4,*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 471-486, 2021, DOI:10.32604/cmc.2021.018239 - 04 June 2021

    Abstract Electroencephalography is a common clinical procedure to record brain signals generated by human activity. EEGs are useful in Brain controlled interfaces and other intelligent Neuroscience applications, but manual analysis of these brainwaves is complicated and time-consuming even for the experts of neuroscience. Various EEG analysis and classification techniques have been proposed to address this problem however, the conventional classification methods require identification and learning of specific EEG characteristics beforehand. Deep learning models can learn features from data without having in depth knowledge of data and prior feature identification. One of the great implementations of deep… More >

  • Open Access

    ARTICLE

    Wavelet-based Inclusion Detection in Cantilever Beams

    Zheng Li1,2, Wei Zhang1, Kezhuang Gong1

    CMC-Computers, Materials & Continua, Vol.9, No.3, pp. 209-228, 2009, DOI:10.3970/cmc.2009.009.209

    Abstract In this paper, continuous wavelet transform has been applied to inclusion detection in cantilever beams. By means of FEM, a cantilever beam with an inclusion is subjected to an impact on its free end, and its stress wave propagation process is calculated. Here, two kinds of inclusions which are distinct in material behavior have been discussed. And we change the inclusion's sizes in the beam and set it in three different positions to simulate some complicated situations. For soft inclusion, the results show that the arrival times of incident and reflective wave are distinguishable by… More >

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