Article
Automation & Control Systems
ChunLi Li, Qintai Hu, Shuping Zhao, Jigang Wu, Jianbin Xiong
Summary: Efficient and accurate diagnosis of rotating machinery in the petrochemical industry is crucial. However, the nonlinear and non-stationary vibration signals generated in harsh environments pose challenges in distinguishing fault signals from normal ones. This paper proposes a BP-Incremental Broad Learning System (BP-INBLS) model to address these challenges. The effectiveness of the proposed method in fault diagnosis is demonstrated through validation and comparative analysis with a published method.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Engineering, Multidisciplinary
Baozhu Zhang, Wenchun Jiang, Yun Luo, Wei Peng, Yingjie Qiao
Summary: This paper studies the distribution of residual stress in thick wall girth welds using narrow-gap welding. The study finds that the heat input, wall thickness, radius thickness ratio, and number of welding passes have an effect on residual stress. A model for the distribution of welding residual stress through the wall thickness is proposed, and its results are in good agreement with finite element calculation results.
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
(2024)
Article
Engineering, Multidisciplinary
Zhihao Zhai, Chengbiao Cai, Qinglai Zhang, Shengyang Zhu
Summary: This paper investigates the effect of localized cracks induced by environmental factors on the dynamic performance and service life of ballastless track in high-speed railways. A mathematical approach for forced vibrations of Mindlin plates with a side crack is derived and implemented into a train-track coupled dynamic system. The accuracy of this approach is verified by comparing with simulation and experimental results, and the dynamic behavior of the side crack under different conditions is analyzed.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Automation & Control Systems
Carmen Bisogni, Lucia Cimmino, Michele Nappi, Toni Pannese, Chiara Pero
Summary: This paper presents a gait-based emotion recognition method that does not rely on facial cues, achieving competitive performance on small and unbalanced datasets. The proposed approach utilizes advanced deep learning architecture and achieves high recognition and accuracy rates.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Engineering, Multidisciplinary
Abraham Mensah, Srinivas Sriramula
Summary: This paper proposes a pathway for developing efficient performance functions to evaluate the probability of failure for interacting pipeline corrosion clustering defects using a probabilistic finite element-based reliability method. The framework reduces computational cost and offers informed decision-making on risk and maintenance management.
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
(2024)
Article
Engineering, Multidisciplinary
Hao Wu, Jie Sun, Wen Peng, Lei Jin, Dianhua Zhang
Summary: This study establishes an analytical model for the coupling of temperature, deformation, and residual stress to explore the mechanism of residual stress formation in hot-rolled strip and how to control it. The accuracy of the model is verified by comparing it with a finite element model, and a method to calculate the critical exit crown ratio to maintain strip flatness is proposed.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Xiangyu Sha, Aizhong Lu, Ning Zhang
Summary: This paper investigates the stress and displacement of a layered soil with a fractional-order viscoelastic model under time-varying loads. The correctness of the solutions is validated using numerical methods and comparison with existing literature. The research findings are of significant importance for exploring soil behavior and its engineering applications under time-varying loads.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Shengwen Tu, Naoki Morita, Tsutomu Fukui, Kazuki Shibanuma
Summary: This study aimed to extend the finite element method to cope with elastic-plastic problems by introducing the s-version FEM. The s-version FEM, which overlays a set of local mesh with fine element size on the conventional FE mesh, simplifies domain discretisation and provides accurate numerical predictions. Previous applications of the s-version FEM were limited to elastic problems, lacking instructions for stress update in plasticity. This study presents detailed instructions and formulations for addressing plasticity problems with the s-version FEM and analyzes a stress concentration problem with linear/nonlinear material properties.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Automation & Control Systems
Jiao Zhu, Sugen Chen, Yufei Liu, Cong Hu
Summary: This study proposes a novel energy-based structural least squares twin support vector clustering algorithm (ESLSTWSVC), which improves clustering performance and efficiency by introducing within-class covariance matrix and solving system of linear equations.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Yixiong Feng, Zetian Zhao, Bingtao Hu, Yong Wang, Hengyuan Si, Zhaoxi Hong, Jianrong Tan
Summary: This paper proposes an innovative method for condition monitoring of nuclear turbines. By redesigning time augmented matrices and building a dynamic auto-regressive model, this method can accurately monitor the working condition of nuclear turbines, thus enhancing the safety and reliability of nuclear power plants.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Engineering, Multidisciplinary
Zhi Yong Ai, Yong Zhi Zhao
Summary: This paper investigates the thermo-hydro-mechanical (THM) problem of layered porous media using the transformed differential quadrature method (TDQM). By transforming the governing equations in cylindrical coordinates and discretizing the temporal and spatial domains, the partial differential equations are converted into algebraic equations. Through the introduction of load conditions, boundary conditions, and continuity conditions, the matrix equation to solve the coupled THM problem is obtained. Case studies are conducted to verify the TDQM solution and discuss the influences of thermal and hydraulic parameters on the THM behaviors of layered porous media.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
James Vidler, Andrei Kotousov, Ching-Tai Ng
Summary: The far-field methodology, developed by J.C. Maxwell, is utilized to estimate the effective third order elastic constants of composite media containing random distribution of spherical particles. The results agree with previous studies and can be applied to homogenization problems in other fields.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Duy-Khuong Ly, Ho-Nam Vu, Chanachai Thongchom, Nguyen-Thoi Trung
Summary: This paper presents a novel numerical approach for nonlinear analysis and smart damping control in laminated functionally graded carbon nanotube reinforced magneto-electro-elastic (FG-CNTMEE) plate structures, taking into account multiple physical fields. The approach employs a multi-physical coupling isogeometric formulation to accurately capture the nonlinear strain-displacement relationship and the magneto-electro-elastic coupling properties. The smart constrained layer damping treatment is applied to achieve nonlinear damped responses. The formulation is transformed into the Laplace domain and converted back to the time domain through inverse techniques for smart control using viscoelastic materials.
ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS
(2024)
Article
Automation & Control Systems
Hao Chen, Jieyu Zhao, Kangxin Chen, Yu Chen
Summary: This paper proposes a self-supervised spherical vector network that learns the orientation perception from 3D point clouds through experience. The proposed network utilizes density-aware adaptive sampling and spherical convolutional vector layers for handling and extraction. Experimental results demonstrate the effectiveness of the method in canonical orientation estimation.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Zhaohui Jiang, Jinshi Liu, Zhiwen Chen, Weichao Luo, Chaobo Zhang, Weihua Gui
Summary: In this paper, a method for estimating the overall particle size distribution (PSD) based on mechanistic modeling and local-global fused prediction networks is proposed. The method can accurately predict the PSD in harsh production environments with limited detection conditions.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
S. Lyaqini, A. Hadri, A. Ellahyani, M. Nachaoui
Summary: In this paper, an improved version of Twin SVM using a non-smooth optimization method is proposed. The proposed approach solves the problem of limited handle Gaussian noise, exaggerated influence of outliers and inability to handle unbalanced data in Twin SVM. By transforming the two-constraint optimization models into an unconstrained non-smooth optimization problem and using the primal dual method to solve it, the proposed approach demonstrates its effectiveness and applicability through experiments on different datasets.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Dmitry Yudin, Nikita Zakharenko, Artem Smetanin, Roman Filonov, Margarita Kichik, Vladislav Kuznetsov, Dmitry Larichev, Evgeny Gudov, Semen Budennyy, Aleksandr Panov
Summary: This research aims to improve waste recycling efficiency through deep learning applications and reduce carbon emissions from computing devices. A diverse dataset is developed for training and evaluating the performance of neural networks in waste recognition, classification, and segmentation tasks.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Jih-Chang Wang, Ting-Yu Chen
Summary: This research aims to create a C-IF VIKOR decision-support method to handle multiple-criteria compromise solutions with circular intuitionistic fuzzy (C-IF) uncertainties. The study focuses on enhancing the augmented scoring function and Chebyshev distance metric in C-IF surroundings to determine the finest compromise solution.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Engineering, Multidisciplinary
Wu Ce Xing, Jiaxing Wang, Yan Qing Wang
Summary: This paper proposes an effective mathematical model for bolted flange joints to study their vibration characteristics. By modeling the flange and bolted joints, governing equations are derived. Experimental studies confirm that the model can accurately predict the vibration characteristics of multiple-plate structures.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Pingchao Yu, Li Hou, Ke Jiang, Zihan Jiang, Xuanjun Tao
Summary: This paper investigates the imbalance problem in rotating machinery and finds that mass imbalance can induce lateral-torsional coupling vibration. By developing a model and conducting detailed analysis, it is discovered that mass imbalance leads to nonlinear time-varying characteristics and there is no steady-state torsional vibration in small unbalanced rotors. Under largely unbalanced conditions, both resonant and unstable behavior can be observed, and increasing lateral damping can suppress instability and reduce lateral amplitude in the resonance region.
APPLIED MATHEMATICAL MODELLING
(2024)
