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  • Open Access

    ARTICLE

    Dynamic Reliability Evaluation and Life Prediction of Transmission System of Multi-Performance Degraded Wind Turbine

    Rong Yuan1, Ruitao Chen2, Haiqing Li3,*, Wenke Yang1, Xiaoxiao Li1

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2331-2347, 2023, DOI:10.32604/cmes.2023.023788

    Abstract Wind power is a kind of important green energy. Thus, wind turbines have been widely utilized around the world. Wind turbines are composed of many important components. Among these components, the failure rate of the transmission system is relatively high in wind turbines. It is because the components are subjected to aerodynamic loads for a long time. In addition, its inertial load will result in fatigue fracture, wear and other problems. In this situation, wind turbines have to be repaired at a higher cost. Moreover, the traditional reliability methods are difficult to deal with the above challenges when performing the… More >

  • Open Access

    ARTICLE

    An Analysis Model of Learners’ Online Learning Status Based on Deep Neural Network and Multi-Dimensional Information Fusion

    Mingyong Li1, Lirong Tang1, Longfei Ma1, Honggang Zhao1, Jinyu Hu1, Yan Wei1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2349-2371, 2023, DOI:10.32604/cmes.2023.022604

    Abstract The learning status of learners directly affects the quality of learning. Compared with offline teachers, it is difficult for online teachers to capture the learning status of students in the whole class, and it is even more difficult to continue to pay attention to students while teaching. Therefore, this paper proposes an online learning state analysis model based on a convolutional neural network and multi-dimensional information fusion. Specifically, a facial expression recognition model and an eye state recognition model are constructed to detect students’ emotions and fatigue, respectively. By integrating the detected data with the homework test score data after… More >

  • Open Access

    ARTICLE

    Quantification of Ride Comfort Using Musculoskeletal Mathematical Model Considering Vehicle Behavior

    Junya Tanehashi1, Szuchi Chang2, Takahiro Hirosei3, Masaki Izawa2, Aman Goyal2, Ayumi Takahashi4, Kazuhito Misaji4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2287-2306, 2023, DOI:10.32604/cmes.2023.022432

    Abstract This research aims to quantify driver ride comfort due to changes in damper characteristics between comfort mode and sport mode, considering the vehicle’s inertial behavior. The comfort of riding in an automobile has been evaluated in recent years on the basis of a subjective sensory evaluation given by the driver. However, reflecting driving sensations in design work to improve ride comfort is abstract in nature and difficult to express theoretically. Therefore, we evaluated the human body’s effects while driving scientifically by quantifying the driver’s behavior while operating the steering wheel and the behavior of the automobile while in motion using… More > Graphic Abstract

    Quantification of Ride Comfort Using Musculoskeletal Mathematical Model Considering Vehicle Behavior

  • Open Access

    REVIEW

    Analytical Models of Concrete Fatigue: A State-of-the-Art Review

    Xiaoli Wei1, D. A. Makhloof1,2, Xiaodan Ren1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 9-34, 2023, DOI:10.32604/cmes.2022.020160

    Abstract Fatigue failure phenomena of the concrete structures under long-term low amplitude loading have attracted more attention. Some structures, such as wind power towers, offshore platforms, and high-speed railways, may resist millions of cycles loading during their intended lives. Over the past century, analytical methods for concrete fatigue are emerging. It is concluded that models for the concrete fatigue calculation can fall into four categories: the empirical model relying on fatigue tests, fatigue crack growth model in fracture mechanics, fatigue damage evolution model based on damage mechanics and advanced machine learning model. In this paper, a detailed review of fatigue computing… More >

  • Open Access

    ARTICLE

    Recent Advances in Fatigue Detection Algorithm Based on EEG

    Fei Wang1,2, Yinxing Wan1, Man Li1,2, Haiyun Huang1,2, Li Li1, Xueying Hou1, Jiahui Pan1,2, Zhenfu Wen3, Jingcong Li1,2,*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3573-3586, 2023, DOI:10.32604/iasc.2023.029698

    Abstract Fatigue is a state commonly caused by overworked, which seriously affects daily work and life. How to detect mental fatigue has always been a hot spot for researchers to explore. Electroencephalogram (EEG) is considered one of the most accurate and objective indicators. This article investigated the development of classification algorithms applied in EEG-based fatigue detection in recent years. According to the different source of the data, we can divide these classification algorithms into two categories, intra-subject (within the same subject) and cross-subject (across different subjects). In most studies, traditional machine learning algorithms with artificial feature extraction methods were commonly used… More >

  • Open Access

    PROCEEDINGS

    Experimental And Numerical Modelling of Cyclic Softening and Damage Behaviors for a Turbine Rotor Material at Elevated Temperature

    M. Li1,2,*, D.H. Li3, Y. Rae1, W. Sun1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.24, No.1, pp. 1-2, 2022, DOI:10.32604/icces.2022.08759

    Abstract In order to better understand the physical process of deformation and cyclic softening a 12% Cr martensitic stainless steel FV566 has been cyclically tested at high temperature in strain control. Increase in temperature was found to increase the cyclic life, softening rate and viscous stress magnitude. An increase in the dwell time led to the acceleration of the material degradation. The microstructure changes and dominating deformation mechanisms were investigated by means of scanning electron microscopy, electron backscatter diffraction and transmission electron microscopy. The results have revealed a gradual sub-grain coarsening, transformation of lath structure into fine equiaxed sub-grains, and misorientation… More >

  • Open Access

    ARTICLE

    Experimental Study on the Degradation of Bonding Behavior between Reinforcing Bars and Concrete after Corrosion and Fatigue Damage

    Shiqin He*, Jiaxing Zhao, Chunyue Wang, Hui Wang

    Structural Durability & Health Monitoring, Vol.16, No.3, pp. 195-212, 2022, DOI:10.32604/sdhm.2022.08886

    Abstract In marine environments, the durability of reinforced concrete structures such as bridges, which suffer from the coupled effects of corrosion and fatigue damage, is significantly reduced. Fatigue loading can result in severe deterioration of the bonds between reinforcing steel bars and the surrounding concrete, particularly when reinforcing bars are corroded. Uniaxial tension testing was conducted under static loading and fatigue loading conditions to investigate the bonding characteristics between corroded reinforcing bars and concrete. An electrolyte corrosion technique was used to accelerate steel corrosion. The results show that the bond strength was reduced under fatigue loading, although the concrete did not… More >

  • Open Access

    ARTICLE

    An Advanced Control Strategy for Dual-Actuator Driving System in Full-Scale Fatigue Test of Wind Turbine Blades

    Guanhua Wang1, Jinghua Wang1, Xuemei Huang1,*, Leian Zhang1, Weisheng Liu2

    Energy Engineering, Vol.119, No.4, pp. 1649-1662, 2022, DOI:10.32604/ee.2022.019695

    Abstract A new dual-actuator fatigue loading system of wind turbine blades was designed. Compared with the traditional pendulum loading mode, the masses in this system only moved linearly along the loading direction to increase the exciting force. However, the two actuators and the blade constituted a complicated non-linear energy transferring system, which led to the non-synchronization of actuators. On-site test results showed that the virtual spindle synchronous strategy commonly used in synchronous control was undesirable and caused the instability of the blade’s amplitude eventually. A cross-coupled control strategy based on the active disturbance rejection algorithm was proposed. Firstly, a control system… More >

  • Open Access

    ARTICLE

    Real Time Monitoring of Muscle Fatigue with IoT and Wearable Devices

    Anita Gehlot1, Rajesh Singh1, Sweety Siwach2, Shaik Vaseem Akram1, Khalid Alsubhi3, Aman Singh4,*, Irene Delgado Noya4,5, Sushabhan Choudhury2

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 999-1015, 2022, DOI:10.32604/cmc.2022.023861

    Abstract Wearable monitoring devices are in demand in recent times for monitoring daily activities including exercise. Moreover, it is widely utilizing for preventing injuries of athletes during a practice session and in few cases, it leads to muscle fatigue. At present, emerging technology like the internet of things (IoT) and sensors is empowering to monitor and visualize the physical data from any remote location through internet connectivity. In this study, an IoT-enabled wearable device is proposing for monitoring and identifying the muscle fatigue condition using a surface electromyogram (sEMG) sensor. Normally, the EMG signal is utilized to display muscle activity. Arduino… More >

  • Open Access

    ARTICLE

    Aluminum Alloy Fatigue Crack Damage Prediction Based on Lamb Wave-Systematic Resampling Particle Filter Method

    Gaozheng Zhao1, Changchao Liu1, Lingyu Sun1, Ning Yang2, Lei Zhang1, Mingshun Jiang1, Lei Jia1, Qingmei Sui1,*

    Structural Durability & Health Monitoring, Vol.16, No.1, pp. 81-96, 2022, DOI:10.32604/sdhm.2022.016905

    Abstract Fatigue crack prediction is a critical aspect of prognostics and health management research. The particle filter algorithm based on Lamb wave is a potential tool to solve the nonlinear and non-Gaussian problems on fatigue growth, and it is widely used to predict the state of fatigue crack. This paper proposes a method of lamb wave-based early fatigue microcrack prediction with the aid of particle filters. With this method, which the changes in signal characteristics under different fatigue crack lengths are analyzed, and the state- and observation-equations of crack extension are established. Furthermore, an experiment is conducted to verify the feasibility… More >

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