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  • Open Access

    ARTICLE

    Unsupervised Time-series Fatigue Damage State Estimation of Complex Structure Using Ultrasound Based Narrowband and Broadband Active Sensing

    S.Mohanty1, A. Chattopadhyay2, J. Wei3, P. Peralta4

    Structural Durability & Health Monitoring, Vol.5, No.3, pp. 227-250, 2009, DOI:10.3970/sdhm.2009.005.227

    Abstract This paper proposes unsupervised system identification based methods to estimate time-series fatigue damage states in real-time. Ultrasound broadband input is used for active damage interrogation. Novel damage index estimation techniques based on dual sensor signals are proposed. The dual sensor configuration is used to remove electrical noise, as well as to improve spatial resolution in damage state estimation. The scalar damage index at any particular damage condition is evaluated using nonparametric system identification techniques, which includes an empirical transfer function estimation approach and a correlation analysis approach. In addition, the effectiveness of two sensor configurations (configuration 1: sensors placed near… More >

  • Open Access

    ARTICLE

    Real Time Damage State Estimation and Condition Based Residual Useful Life Estimation of a Metallic Specimen under Biaxial Loading

    S.Mohanty1, A. Chattopadhyay2, J. Wei3, P. Peralta4

    Structural Durability & Health Monitoring, Vol.5, No.1, pp. 33-56, 2009, DOI:10.3970/sdhm.2009.005.033

    Abstract The current state of the art in the area of real time structural health monitoring techniques offers adaptive damage state prediction and residual useful life assessment. The present paper discusses the use of an integrated prognosis model, which combines an on-line state estimation model with an off-line predictive model to adaptively estimate the residual useful life of an Al-6061 cruciform specimen under biaxial loading. The overall fatigue process is assumed to be a slow time scale process compared to the time scale at which, the sensor signals were acquired for on-line state estimation. The on-line state estimation model was based… More >

  • Open Access

    ARTICLE

    Novel DDoS Feature Representation Model Combining Deep Belief Network and Canonical Correlation Analysis

    Chen Zhang1, Jieren Cheng1,2,3,*, Xiangyan Tang1, Victor S. Sheng4, Zhe Dong1, Junqi Li1

    CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 657-675, 2019, DOI:10.32604/cmc.2019.06207

    Abstract Distributed denial of service (DDoS) attacks launch more and more frequently and are more destructive. Feature representation as an important part of DDoS defense technology directly affects the efficiency of defense. Most DDoS feature extraction methods cannot fully utilize the information of the original data, resulting in the extracted features losing useful features. In this paper, a DDoS feature representation method based on deep belief network (DBN) is proposed. We quantify the original data by the size of the network flows, the distribution of IP addresses and ports, and the diversity of packet sizes of different protocols and train the… More >

  • Open Access

    ARTICLE

    Correlation Analysis of Control Parameters of Flotation Process

    Yanpeng Wu1, Xiaoqi Peng1,*, Nur Mohammad2

    Journal on Internet of Things, Vol.1, No.2, pp. 63-69, 2019, DOI:10.32604/jiot.2019.06111

    Abstract The dosage of gold-antimony flotation process of 5 main drugs, including Copper Sulfate, Lead Nitrate, Yellow Medicine, No. 2 Oil, Black Medicine, with corresponding visual features of foam images, including Stability, Gray Scale, Mean R, Mean G, Mean B, Mean Average, Dimension and Degree Variance, were recorded. Parameter correlation analysis showed that the correlation among Copper Sulfate, Yellow Medicine, Black Medicine, as well as the correlation among Gray Scale, Mean R, Mean G, Mean B, is strong, and the correlation among Dimension, Gray Scale, Mean R, Mean G, Mean B, as well as the correlation between Stability and each dosing… More >

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