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  • Open Access

    ARTICLE

    Impact Damage Identification of Aluminum Alloy Reinforced Plate Based on GWO-ELM Algorithm

    Wei Li1,2, Benjian Zou1, Yuxiang Luo2, Ning Yang2, Faye Zhang1,*, Mingshun Jiang1, Lei Jia1

    Structural Durability & Health Monitoring, Vol.17, No.6, pp. 485-500, 2023, DOI:10.32604/sdhm.2023.025989

    Abstract As a critical structure of aerospace equipment, aluminum alloy stiffened plate will influence the stability of spacecraft in orbit and the normal operation of the system. In this study, a GWO-ELM algorithm-based impact damage identification method is proposed for aluminum alloy stiffened panels to monitor and evaluate the damage condition of such stiffened panels of spacecraft. Firstly, together with numerical simulation, the experimental simulation to obtain the damage acoustic emission signals of aluminum alloy reinforced panels is performed, to establish the damage data. Subsequently, the amplitude-frequency characteristics of impact damage signals are extracted and put into an extreme learning machine… More >

  • Open Access

    ARTICLE

    Nonlinear Correction of Pressure Sensor Based on Depth Neural Network

    Yanming Wang1,2,3, Kebin Jia1,2,3,*, Pengyu Liu1,2,3

    Journal on Internet of Things, Vol.2, No.3, pp. 109-120, 2020, DOI:10.32604/jiot.2020.010138

    Abstract With the global climate change, the high-altitude detection is more and more important in the climate prediction, and the input-output characteristic curve of the air pressure sensor is offset due to the interference of the tested object and the environment under test, and the nonlinear error is generated. Aiming at the difficulty of nonlinear correction of pressure sensor and the low accuracy of correction results, depth neural network model was established based on wavelet function, and Levenberg-Marquardt algorithm is used to update network parameters to realize the nonlinear correction of pressure sensor. The experimental results show that compared with the… More >

  • Open Access

    ARTICLE

    A Control Algorithm for the Optimization of Batch Reactor-Based Processes

    Yanling Bai1,*, Feng Liu2

    FDMP-Fluid Dynamics & Materials Processing, Vol.15, No.4, pp. 307-319, 2019, DOI:10.32604/fdmp.2019.07833

    Abstract Levenberg-Marquardt (LM) algorithm is applied for the optimization of the heat transfer of a batch reactor. The validity of the approach is verified through comparison with experimental results. It is found that the mathematical model can properly describe the heat transfer relationships characterizing the considered system, with the error being kept within ±2°C. Indeed, the difference between the actual measured values and the model calculated value curve is within ±1.5°C, which is in agreement with the model assumptions and demonstrates the reliability and effectiveness of the algorithm applied to the batch reactor heat transfer model. Therefore, the present work provides… More >

  • Open Access

    ARTICLE

    Assessing the Forecasting of Comprehensive Loss Incurred by Typhoons: A Combined PCA and BP Neural Network Model

    Shuai Yuan1, Guizhi Wang1,*, Jibo Chen1, Wei Guo2

    Journal on Artificial Intelligence, Vol.1, No.2, pp. 69-88, 2019, DOI:10.32604/jai.2019.06535

    Abstract This paper develops a joint model utilizing the principal component analysis (PCA) and the back propagation (BP) neural network model optimized by the Levenberg Marquardt (LM) algorithm, and as an application of the joint model to investigate the damages caused by typhoons for a coastal province, Fujian Province, China in 2005-2015 (latest). First, the PCA is applied to analyze comprehensively the relationship between hazard factors, hazard bearing factors and disaster factors. Then five integrated indices, overall disaster level, typhoon intensity, damaged condition of houses, medical rescue and self-rescue capability, are extracted through the PCA; Finally, the BP neural network model,… More >

  • Open Access

    ARTICLE

    Impact Damage Identification for Composite Material Based on Transmissibility Function and OS-ELM Algorithm

    Yajie Sun1,2,*, Yanqing Yuan2, Qi Wang2, Sai Ji1,2, Lihua Wang3, Shaoen Wu4, Jie Chen2, Qin Zhang2

    Journal of Quantum Computing, Vol.1, No.1, pp. 1-8, 2019, DOI:10.32604/jqc.2019.05788

    Abstract A method is proposed based on the transmissibility function and the Online Sequence Extreme Learning Machine (OS-ELM) algorithm, which is applied to the impact damage of composite materials. First of all, the transmissibility functions of the undamaged signals and the damage signals at different points are calculated. Secondly, the difference between them is taken as the damage index. Finally, principal component analysis (PCA) is used to reduce the noise feature. And then, input to the online sequence limit learning neural network classification to identify damage and confirm the damage location. Taking the amplitude of the transmissibility function instead of the… More >

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