Journal Description
Machines
Machines
is an international, peer-reviewed, open access journal on machinery and engineering published monthly online by MDPI. The IFToMM is affiliated with Machines and its members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Inspec, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Mechanical)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 15.6 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
2.6 (2022);
5-Year Impact Factor:
2.8 (2022)
Latest Articles
Re-Entrant Green Scheduling Problem of Bearing Production Shops Considering Job Reworking
Machines 2024, 12(4), 281; https://doi.org/10.3390/machines12040281 - 22 Apr 2024
Abstract
To solve various reworking and repair problems caused by unqualified bearing product quality inspections, this paper introduces a green re-entrant scheduling optimization method for bearing production shops considering job reworking. By taking into account quality inspection constraints, this paper establishes an integrated scheduling
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To solve various reworking and repair problems caused by unqualified bearing product quality inspections, this paper introduces a green re-entrant scheduling optimization method for bearing production shops considering job reworking. By taking into account quality inspection constraints, this paper establishes an integrated scheduling mathematical model based on the entire processing–transportation–assembly process of bearing production shops with the goals for minimizing the makespan, total carbon emissions, and waste emissions. To solve these problems, the concepts of the set of the longest common machine routes (SLCMR) and the set of the shortest recombination machine combinations (SSRMC) were used to propose the re-entrant scheduling optimization method, based on system reconfiguration, to enhance the system stability and production scheduling efficiency. Then, a multi-objective hybrid optimization algorithm, based on a neighborhood local search (MOOA-LS), is proposed to improve the search scope and optimization ability by constructing a multi-level neighborhood search structure. Finally, this paper takes a bearing production shop as an example to carry out the case study and designs a series of experimental analyses and comparative tests. The final results show that in the bearing production process, the proposed model and algorithm can effectively realize green and energy-saving re-entrant manufacturing scheduling.
Full article
(This article belongs to the Special Issue Smart Manufacturing Systems and Processes)
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Study on Performance Improvement through Reducing Axial Force of Ferrite Double-Layer Spoke-Type Permanent Magnet Synchronous Motor with Core Skew
by
Dong-Woo Nam, Kangbeen Lee, Si-Woo Song, Won-Ho Kim and Jae-Jun Lee
Machines 2024, 12(4), 280; https://doi.org/10.3390/machines12040280 - 22 Apr 2024
Abstract
Recently, due to the price fluctuation and supply instability of rare earth mineral resources, there has been a lot of development of electric motors using non-rare-earth permanent magnets. As a result, motors using Dy-free permanent magnets and ferrite permanent magnets are being researched,
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Recently, due to the price fluctuation and supply instability of rare earth mineral resources, there has been a lot of development of electric motors using non-rare-earth permanent magnets. As a result, motors using Dy-free permanent magnets and ferrite permanent magnets are being researched, and, in particular, ferrite permanent magnets often utilize spoke-type structures, which are magnetic flux concentrators, to compensate for their low coercivity and residual flux density. However, in general, spoke-type PMSMs do not use much reluctance torque, so double-layer spoke-type PMSMs have been studied for their more efficient design. Unlike general spoke-type PMSMs, double-layer spoke-type PMSMs can utilize high reluctance torque by increasing the difference between d-axis and q-axis reluctance. However, as the difference in magnetic resistance increases, vibration and noise are generated, which adversely affects the mechanical part and shortens the life of the motor. Although this problem seemed to be solved by applying core skew in the previous study, it was confirmed that the axial force caused by the axial leakage flux occurred in the maximum torque per ampere (MTPA) control section and the torque ripple was increased. Therefore, in this paper, a model that can apply symmetrical core skew and reduce axial force is proposed. First, the causes of the axial force generated in previous studies were analyzed. Based on the analysis of these causes, a new symmetrical core skew structure was proposed, and its justification was verified through FEA.
Full article
(This article belongs to the Special Issue Advances and Trends in PM-Free or Rare-Earth-Free PM Motors)
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Open AccessArticle
Validation Challenges in Data for Different Diesel Engine Performance Regimes Utilising HVO Fuel: A Study on the Application of Artificial Neural Networks for Emissions Prediction
by
Jonas Matijošius, Alfredas Rimkus and Alytis Gruodis
Machines 2024, 12(4), 279; https://doi.org/10.3390/machines12040279 - 21 Apr 2024
Abstract
Artificial neural networks (ANNs) provide supervised learning via input pattern assessment and effective resource management, thereby improving energy efficiency and predicting environmental fluctuations. The advanced technique of ANNs forecasts diesel engine emissions by collecting measurements during trial sessions. This study included experimental sessions
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Artificial neural networks (ANNs) provide supervised learning via input pattern assessment and effective resource management, thereby improving energy efficiency and predicting environmental fluctuations. The advanced technique of ANNs forecasts diesel engine emissions by collecting measurements during trial sessions. This study included experimental sessions to establish technical and ecological indicators for a diesel engine across several operational scenarios. VALLUM01, a novel tool, has been created with a user-friendly interface for data input/output, intended for the purposes of testing and prediction. There was a comprehensive collection of 12 input parameters and 10 output parameters that were identified as relevant and sufficient for the objectives of training, validation, and prediction. The proper value ranges for transforming into fuzzy sets for input/output to an ANN were found. Given that the ANN’s training session comprises 1,000,000 epochs and 1000 perceptrons within a single-hidden layer, its effectiveness can be considered high. Many statistical distributions, including Pearson, Spearman, and Kendall, validate the prediction accuracy. The accuracy ranges from 96% on average, and in some instances, it may go up to 99%.
Full article
(This article belongs to the Special Issue Cutting-Edge Technologies and Applications in Automatic Control Systems)
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An Investigation of Real-Time Robotic Polishing Motion Planning Using a Dynamical System
by
Xinqing Wang, Xin Wang, Zhenyu Yang and Yupeng Zou
Machines 2024, 12(4), 278; https://doi.org/10.3390/machines12040278 - 21 Apr 2024
Abstract
When addressing the technical challenges of achieving precise force tracking during the local polishing process of polishing robots, controlling the contact state between the robot and the workpiece surface is essential. To this end, a contact motion-planning strategy based on dynamic systems is
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When addressing the technical challenges of achieving precise force tracking during the local polishing process of polishing robots, controlling the contact state between the robot and the workpiece surface is essential. To this end, a contact motion-planning strategy based on dynamic systems is designed to generate trajectory routes during local polishing. The trajectory simulation of the local modulation dynamic system is achieved through the employment of the support vector regression (SVR) algorithm with a Gaussian kernel, facilitating the learning process. The feasibility and stability of planning local paths are validated using the local modulation dynamic system. To maintain a constant contact force between the end-effector polishing robot and the workpiece, an integral adaptive impedance control strategy is utilized, enabling the robot’s compliant control. Subsequently, an experimental system for the polishing robot is constructed in order to verify the effectiveness of the motion-planning system. The experimental results demonstrate that the proposed motion-planning approach is applicable in practical polishing processes, ensuring smooth contact and maintaining the desired contact force when scanning nonlinear surfaces, and thus showcasing stability and practicality.
Full article
(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)
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On the Integrity of Large-Scale Direct-Drive Wind Turbine Electrical Generator Structures: An Integrated Design Methodology for Optimisation, Considering Thermal Loads and Novel Techniques
by
Magnus Bichan, Pablo Jaen-Sola, Daniel Gonzalez-Delgado and Erkan Oterkus
Machines 2024, 12(4), 277; https://doi.org/10.3390/machines12040277 - 21 Apr 2024
Abstract
With the rapid expansion of offshore wind capacity worldwide, minimising operation and maintenance requirements is pivotal. Regarded as a low-maintenance alternative to conventional drivetrain systems, direct-drive generators are increasingly commonplace for wind turbines in hard-to-service areas. To facilitate higher torque requirements consequent to
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With the rapid expansion of offshore wind capacity worldwide, minimising operation and maintenance requirements is pivotal. Regarded as a low-maintenance alternative to conventional drivetrain systems, direct-drive generators are increasingly commonplace for wind turbines in hard-to-service areas. To facilitate higher torque requirements consequent to low-speed operation, these machines are bulky, greatly increasing nacelle size and mass over their counterparts. This paper therefore details the structural optimisation of the International Energy Agency 15 MW Reference Wind Turbine rotor through iterative Parameter and Topology Optimisation and the inclusion of additional structural members, with consideration to its mechanical, modal, and thermal performances. With temperature found to have a significant impact on the structural integrity of multi-megawatt direct-drive machines, a Computational Fluid Dynamics analysis was carried out to map the temperature of the structure during operation and inform a consequent Finite Element Method analysis. This process, novel to this paper, found that topologically optimised structures outperform parametrically optimised structures thermally and that integrated heatsinks can be employed to further reduce deformation. Lastly, generative design techniques were used to further optimise the structure, reducing its mass, deformation, and maximum stress and expanding its operating envelope. This study reaches several key conclusions, demonstrating that significant mass reductions are achievable through the removal of cylinder wall geometry areas as well as through the implementation of structural supports and iterative parametric and topology optimisation techniques. Through the flexibility it grants, generative design was found to be a powerful tool, delivering further improvements to an already efficient, yet complex design. Heatsinks were found to lower generator structural temperatures, which may yield lower active cooling requirements whilst providing structural support. Lastly, the link between the increased mass and the increased financial and environmental impact of the rotor was confirmed.
Full article
(This article belongs to the Special Issue Design and Dynamic Control of Wind Turbines)
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A Real-Time Dual-Task Defect Segmentation Network for Grinding Wheels with Coordinate Attentioned-ASP and Masked Autoencoder
by
Yifan Li, Chuanbao Li, Ping Zhang and Han Wang
Machines 2024, 12(4), 276; https://doi.org/10.3390/machines12040276 - 21 Apr 2024
Abstract
The current network for the dual-task grinding wheel defect semantic segmentation lacks high-precision lightweight designs, making it challenging to balance lightweighting and segmentation accuracy, thus severely limiting its practical application in grinding wheel production lines. Additionally, recent approaches for addressing the natural class
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The current network for the dual-task grinding wheel defect semantic segmentation lacks high-precision lightweight designs, making it challenging to balance lightweighting and segmentation accuracy, thus severely limiting its practical application in grinding wheel production lines. Additionally, recent approaches for addressing the natural class imbalance in defect segmentation fail to leverage the inexhaustible unannotated raw data on the production line, posing huge data wastage. Targeting these two issues, firstly, by discovering the similarity between Coordinate Attention (CA) and ASPP, this study has introduced a novel lightweight CA-ASP module to the DeeplabV3+, which is 45.3% smaller in parameter size and 53.2% lower in FLOPs compared to the ASPP, while achieving better segmentation precision. Secondly, we have innovatively leveraged the Masked Autoencoder (MAE) to address imbalance. By developing a new Hybrid MAE and applying it to self-supervised pretraining on tremendous unannotated data, we have significantly uplifted the network’s semantic understanding on the minority classes, which leads to further rises in both the overall accuracy and accuracy of the minorities without additional computational growth. Lastly, transfer learning has been deployed to fully utilize the highly related dual tasks. Experimental results demonstrate that the proposed methods with a real-time latency of 9.512 ms obtain a superior segmentation accuracy on the mIoU score over the compared real-time state-of-the-art methods, excelling in managing the imbalance and ensuring stability on the complicated scenes across the dual tasks.
Full article
(This article belongs to the Special Issue Application of Deep Learning in Fault Diagnosis)
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Open AccessArticle
Anti-Offset Multicoil Underwater Wireless Power Transfer Based on a BP Neural Network
by
You Fu, Haodong Tang, Jianan Luo and Zhouhua Peng
Machines 2024, 12(4), 275; https://doi.org/10.3390/machines12040275 - 20 Apr 2024
Abstract
Autonomous underwater vehicles (AUVs) are now widely used in both civilian and military applications; however, wireless charging underwater often faces difficulties such as disturbances from ocean currents and errors in device positioning, making proper alignment of the charging devices challenging. Misalignment between the
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Autonomous underwater vehicles (AUVs) are now widely used in both civilian and military applications; however, wireless charging underwater often faces difficulties such as disturbances from ocean currents and errors in device positioning, making proper alignment of the charging devices challenging. Misalignment between the primary and secondary coils can significantly impact the efficiency and power of the wireless charging system energy transfer. To address the issue of misalignment in wireless charging systems, this paper proposes a multiple transfer coil wireless power transfer (MTCWPT) system based on backpropagation (BP) neural network control combined with nonsingular terminal sliding mode control (NTSMC) to enhance further the system robustness and efficiency. To achieve WPT in the ocean, a coil shielding case structure was equipped. In displacement experiments, the proposed multi-transmitting coil system could achieve stable power transfer of 40 W and efficiency of over 78.5% within a displacement range of 8 cm. The system robustness was also validated. This paper presents a new AUV energy supply solution based on MTCWPT. The proposed MTCWPT system can significantly improve the navigation performance of AUVs.
Full article
(This article belongs to the Section Automation and Control Systems)
Open AccessArticle
Research on Dynamic Characteristic Coefficients of Integral Squeeze Film Damper
by
Wei Yan, Jinlong Lu, Jiabao Pan, Jinduo Liu, Chengming Fuyang and Dongdong Ye
Machines 2024, 12(4), 274; https://doi.org/10.3390/machines12040274 - 20 Apr 2024
Abstract
Integral squeeze film damper (ISFD) is a new type of structure that appeared on the basis of traditional squeeze film damper (SFD). Since the oil film in ISFD is a segmented structure without annular flow, the nonlinearity of the oil film force has
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Integral squeeze film damper (ISFD) is a new type of structure that appeared on the basis of traditional squeeze film damper (SFD). Since the oil film in ISFD is a segmented structure without annular flow, the nonlinearity of the oil film force has been improved to a great extent. The dynamic characteristic coefficients of ISFD have a close relationship with its damping performance. This work investigates and studies the dynamic characteristic parameters of ISFD by means of numerical analysis and experimental validation techniques in order to examine the dynamic features and unveil the damping mechanism. The ISFD solid and fluid analysis models are created, and the computational fluid dynamics (CFD) and mechanical performance analyses are completed. The force acting on the ISFD’s S-type elastomer under excitation conditions is revealed in the mechanical property analysis, and the flow characteristics of the internal oil film are investigated in the CFD analysis. It is discovered that the ISFD has good linear damping and stiffness characteristics, and numerical analytical values for the ISFD’s damping and stiffness coefficients are obtained. By constructing a bi-directional excitation test rig, the experimental values of the ISFD stiffness coefficient and damping coefficient are determined. These values are in close agreement with the results of the numerical analysis, confirming the accuracy of the ISFD’s numerical analysis conclusions.
Full article
(This article belongs to the Section Machine Design and Theory)
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Ultra-Compact Orthoplanar Spring via Euler-Spiral Flexures
by
Jacob Sutton, Collin Ynchausti, Kyle Dahl, Spencer P. Magleby, Larry L. Howell and Brian D. Jensen
Machines 2024, 12(4), 273; https://doi.org/10.3390/machines12040273 - 18 Apr 2024
Abstract
Orthoplanar springs are single-component compliant mechanisms that can be fabricated from sheet material and undergo deflection orthogonal to the plane of the mechanism. They are useful in applications where spatial constraints are significant. An Euler spiral is a curve whose curvature is linearly
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Orthoplanar springs are single-component compliant mechanisms that can be fabricated from sheet material and undergo deflection orthogonal to the plane of the mechanism. They are useful in applications where spatial constraints are significant. An Euler spiral is a curve whose curvature is linearly proportional to the arc length allowing for the curve to assume a flat position under a load. In this work, orthoplanar spring and Euler-spiral concepts are synthesized to create a single-component spring mechanism that lies flat under a load. Where traditional planar springs under a load will take on an out-of-plane contour, the Euler-spiral orthoplanar spring lies completely flat under a load. The relationship between the load needed to flatten the orthoplanar Euler-spiral spring and its physical geometry is examined. A use case where the Euler-spiral orthoplanar spring is utilized as a deployment mechanism for a mid-flight emerging antenna on the surface of a flight body is presented.
Full article
(This article belongs to the Special Issue Optimization and Design of Compliant Mechanisms)
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Robust Combined Adaptive Passivity-Based Control for Induction Motors
by
Juan Carlos Travieso-Torres, Abdiel Josadac Ricaldi-Morales and Norelys Aguila-Camacho
Machines 2024, 12(4), 272; https://doi.org/10.3390/machines12040272 - 18 Apr 2024
Abstract
The need for industrial and commercial machinery to maintain high torque while accurately following a variable angular speed is increasing. To meet this demand, induction motors (IMs) are commonly used with variable speed drives (VSDs) that employ a field-oriented control (FOC) scheme. Over
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The need for industrial and commercial machinery to maintain high torque while accurately following a variable angular speed is increasing. To meet this demand, induction motors (IMs) are commonly used with variable speed drives (VSDs) that employ a field-oriented control (FOC) scheme. Over the last thirty years, IMs have been replacing independent connection direct current motors due to their cost-effectiveness, reduced maintenance needs, and increased efficiency. However, IMs and VSDs exhibit nonlinear behavior, uncertainties, and disturbances. This paper proposes a robust combined adaptive passivity-based control (CAPBC) for this class of nonlinear systems that applies to angular rotor speed and stator current regulation inside an FOC scheme for IMs’ VSDs. It uses general Lyapunov-based design energy functions and adaptive laws with -modification to assure robustness after combining control and monitoring variables. Lyapunov’s second method and the Barbalat Lemma prove that the control and identification error tends to be zero over time. Moreover, comparative experimental results with a standard proportional–integral controller (PIC) and direct APBC show the proposed CAPBC’s effectiveness and robustness under normal and changing conditions.
Full article
(This article belongs to the Special Issue Robust Control of Permanent Magnet Synchronous Motors (PMSM) and Induction Motors (IM))
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A Liquid Nitrogen Cooling Circulation Unit: Its Design and a Performance Study
by
Jianjie Yao, Xiangyou Lu, Yuanlai Xie, Qianxu Wang and Xiao Liu
Machines 2024, 12(4), 271; https://doi.org/10.3390/machines12040271 - 18 Apr 2024
Abstract
A liquid nitrogen cooling circulating unit is a necessary condition for the stable operation of a cryogenic oscillator, which can provide a stable working environment for the oscillator. In this paper, according to the user’s functional requirements and performance parameters, a closed cooling
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A liquid nitrogen cooling circulating unit is a necessary condition for the stable operation of a cryogenic oscillator, which can provide a stable working environment for the oscillator. In this paper, according to the user’s functional requirements and performance parameters, a closed cooling system with supercooled liquid nitrogen as the medium was designed using SOLIDWORKS 2021 software, which can provide a suitable working environment for the cryogenic oscillator. Combined with the system heat load analysis, theoretical calculation for and the design of the coil heat exchanger, one of the core pieces of equipment of the unit, were carried out. The performance of the designed nitrogen exhaust heater was studied using FLUENT 2021 software, and the velocity field and temperature field of the nitrogen exhaust heater were analyzed. The results show that the outlet temperature of the nitrogen exhaust heating device can reach up to 310 K, and the outlet flow rate of the heating device is 0.01528 kg/s. The experiments on the liquid nitrogen circulating unit using the simulated load equipment show that the refrigeration power of the unit can reach a design index of 600 W, and the temperature of the liquid nitrogen at the liquid outlet of the unit can reach 77.8 K. The experiments also show that the unit meets the design requirements.
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(This article belongs to the Section Machine Design and Theory)
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RBF-Based Fractional-Order SMC Fault-Tolerant Controller for a Nonlinear Active Suspension
by
Weipeng Zhao and Liang Gu
Machines 2024, 12(4), 270; https://doi.org/10.3390/machines12040270 - 18 Apr 2024
Abstract
Active suspension control technologies have become increasingly significant in improving suspension performance for driving stability and comfort. An RBF-based fractional-order SMC fault-tolerant controller is developed in this research to guarantee ride comfort and handling stability when faced with the partial loss of actuator
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Active suspension control technologies have become increasingly significant in improving suspension performance for driving stability and comfort. An RBF-based fractional-order SMC fault-tolerant controller is developed in this research to guarantee ride comfort and handling stability when faced with the partial loss of actuator effectiveness due to failure. To obtain better control performance, fractional-order theory and the RBF algorithm are discussed to solve the jitter vibration problem in SMC, and the RBF is exploited to obtain a more appropriate switching gain. First, a half-nonlinear active suspension model and a fault car model are presented. Then, the design process of the RBF-based fractional-order SMC fault-tolerant controller is described. Next, a simulation is presented to demonstrate the effectiveness of the proposed strategy. According to the simulation, the proposed method can improve performance in the case of a healthy suspension, and the fault-tolerant controller can guarantee the capabilities when actuators go wrong.
Full article
(This article belongs to the Special Issue Intelligent Control and Active Safety Techniques for Road Vehicles)
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Study on the Evolution of Sealing Performance during the Start-Up Process of Dynamic Pressure Seals Based on Three-Dimensional Fractal Functions
by
Enzhe Bi, Shuangxi Li, Jiangteng Zhang and An Liu
Machines 2024, 12(4), 269; https://doi.org/10.3390/machines12040269 - 17 Apr 2024
Abstract
A model based on a three-dimensional fractal function is developed and used in conjunction with experiments to analyze the evolutionary pattern of sealing performance during the start-up process of dynamic pressure seals, and the influence of end-face microscopic features on the evolution law
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A model based on a three-dimensional fractal function is developed and used in conjunction with experiments to analyze the evolutionary pattern of sealing performance during the start-up process of dynamic pressure seals, and the influence of end-face microscopic features on the evolution law is discussed. It is found that the opening state of the seal is divided into three stages: the non-opened stage, transition stage, and full-opened stage. The isotropic dimensions of the cavities have a coupling effect on the leakage, and they diminish as the speed increases. In order to enhance the sealing performance during start-up, it is suggested that the seal faces have a fractal dimension of 2.4 to 2.6, and a characteristic factor of less than 1 × 10−9 m.
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(This article belongs to the Section Advanced Manufacturing)
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Three-Dimensional Modeling for Mechanical Analysis of Hydropower Generators with Floating Rotor Rim
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David Rondon, Simon Pääjärvi, Jan-Olov Aidanpää, Rolf Gustavsson and Peter Jeppsson
Machines 2024, 12(4), 268; https://doi.org/10.3390/machines12040268 - 17 Apr 2024
Abstract
Hydropower generators withstand multiple forces from diverse sources during operation. To ensure their stability and safe performance, numerical tools are developed to characterize their dynamic properties. Traditionally, generators are assumed to be rigid in rotordynamic analyses. However, the measurements in power stations challenge
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Hydropower generators withstand multiple forces from diverse sources during operation. To ensure their stability and safe performance, numerical tools are developed to characterize their dynamic properties. Traditionally, generators are assumed to be rigid in rotordynamic analyses. However, the measurements in power stations challenge this assumption. This article proposes a novel approach to modeling hydropower generators with floating rotor rims using a three-dimensional (3-D) Finite Element Method, aiming to study their dynamic performance and properties, including natural frequencies, the modes of vibrations, and expansion due to centrifugal and electromagnetic forces, with the goal of improving the reliability of modern designs. Both this approach and employing a two-dimensional (2-D) model using curved beams result in similar in-plane natural frequencies and the expansion of the rotor rim due to centrifugal forces. However, the 3-D model can be used to calculate the out-of-plane natural frequencies and modes, to model the dynamics of complex geometries, and to perform stress evaluation and fatigue analysis.
Full article
(This article belongs to the Section Electrical Machines and Drives)
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A Study on the Cavitation Effect of Elastic Material with Textured Surfaces under Fluid Lubrication Conditions
by
Haocheng Sun, Zhijun Yan, Shibo Wu, Ze Liu and Yuanyuan Jiang
Machines 2024, 12(4), 267; https://doi.org/10.3390/machines12040267 - 17 Apr 2024
Abstract
This study investigates the effect of the elastic surface micro-texture on the cavitation and lubrication characteristics of the friction pairs through theoretical and experimental research. Through numerical simulations and experiments, the influences of the elastic modulus and sliding speed on the lubrication performance
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This study investigates the effect of the elastic surface micro-texture on the cavitation and lubrication characteristics of the friction pairs through theoretical and experimental research. Through numerical simulations and experiments, the influences of the elastic modulus and sliding speed on the lubrication performance of the friction pair are studied. The results show that under certain speed and load conditions, the friction coefficient of the elastic texture is smaller, and the lubrication performance is better than that of the rigid texture. Increasing the sliding speed and texture spacing properly can improve the lubrication performance of elastic friction pairs. In addition, as the elastic modulus decreases, the elastic deformation and oil film thickness increase, and the cavitation phenomenon becomes more significant. Thus, the lubrication performance of the friction pair is improved.
Full article
(This article belongs to the Section Material Processing Technology)
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An Intelligent Diagnostic Method for Wear Depth of Sliding Bearings Based on MGCNN
by
Jingzhou Dai, Ling Tian and Haotian Chang
Machines 2024, 12(4), 266; https://doi.org/10.3390/machines12040266 - 16 Apr 2024
Abstract
Sliding bearings are vital components in modern industry, exerting a crucial influence on equipment performance, with wear being one of their primary failure modes. In addressing the issue of wear diagnosis in sliding bearings, this paper proposes an intelligent diagnostic method based on
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Sliding bearings are vital components in modern industry, exerting a crucial influence on equipment performance, with wear being one of their primary failure modes. In addressing the issue of wear diagnosis in sliding bearings, this paper proposes an intelligent diagnostic method based on a multiscale gated convolutional neural network (MGCNN). The proposed method allows for the quantitative inference of the maximum wear depth (MWD) of sliding bearings based on online vibration signals. The constructed model adopts a dual-path parallel structure in both the time and frequency domains to process bearing vibration signals, ensuring the integrity of information transmission through residual network connections. In particular, a multiscale gated convolution (MGC) module is constructed, which utilizes convolutional network layers to extract features from sample sequences. This module incorporates multiple scale channels, including long-term, medium-term, and short-term cycles, to fully extract information from vibration signals. Furthermore, gated units are employed to adaptively assign weights to feature vectors, enabling control of information flow direction. Experimental results demonstrate that the proposed method outperforms the traditional CNN model and shallow machine learning model, offering promising support for equipment condition monitoring and predictive maintenance.
Full article
(This article belongs to the Special Issue Advanced Signal Processing Methods and Deep Neural Networks for Machine Fault Diagnosis)
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A Study of Sliding Friction Using an Acoustic Emission and Wavelet-Based Energy Approach
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Sergey Sychev and Andre D. L. Batako
Machines 2024, 12(4), 265; https://doi.org/10.3390/machines12040265 - 16 Apr 2024
Abstract
The purpose of this work is to study the mechanism of running-in during friction and to determine the informative parameters characterizing the degree of its completion. During friction, contact interaction of rough surfaces causes various wave phenomena covering a wide range of frequencies,
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The purpose of this work is to study the mechanism of running-in during friction and to determine the informative parameters characterizing the degree of its completion. During friction, contact interaction of rough surfaces causes various wave phenomena covering a wide range of frequencies, the subsequent frequency analysis can provide information about the sizes of wave sources and thereby clarify the mechanism of interaction between surface roughness. The using of the wavelet transform for processing the signals of audible acoustic emission made it possible to determine the beginning and the end of the change in the frequency ranges of the interaction of roughness. The code developed by the authors was used to analyze the acoustic emission signals by using wavelet energy and entropy criteria. The mother wavelet was chosen by carefully evaluating the effectiveness of 54 preliminary candidates for the mother wavelet from 7 wavelet families, according to three criteria: (1) maximum wavelet energy; (2) Shannon entropy minimum; and (3) maximum energy-to-Shannon entropy ratio.
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(This article belongs to the Special Issue Innovations in the Design, Simulation, and Manufacturing of Production Systems)
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Open AccessArticle
Autonomous Vehicle Decision and Control through Reinforcement Learning with Traffic Flow Randomization
by
Yuan Lin, Antai Xie and Xiao Liu
Machines 2024, 12(4), 264; https://doi.org/10.3390/machines12040264 - 16 Apr 2024
Abstract
Most of the current studies on autonomous vehicle decision-making and control based on reinforcement learning are conducted in simulated environments. The training and testing of these studies are carried out under the condition of rule-based microscopic traffic flow, with little consideration regarding migrating
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Most of the current studies on autonomous vehicle decision-making and control based on reinforcement learning are conducted in simulated environments. The training and testing of these studies are carried out under the condition of rule-based microscopic traffic flow, with little consideration regarding migrating them to real or near-real environments. This may lead to performance degradation when the trained model is tested in more realistic traffic scenes. In this study, we propose a method to randomize the driving behavior of surrounding vehicles by randomizing certain parameters of the car-following and lane-changing models of rule-based microscopic traffic flow. We trained policies with deep reinforcement learning algorithms under the domain-randomized rule-based microscopic traffic flow in freeway and merging scenes and then tested them separately in rule-based and high-fidelity microscopic traffic flows. The results indicate that the policies trained under domain-randomized traffic flow have significantly better success rates and episodic rewards compared to those trained under non-randomized traffic flow.
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(This article belongs to the Section Vehicle Engineering)
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Scissor Arm for Cambered Snow: Mechanical Theory
by
Shuang Gang, Zhanran Gong, Yiming Li, Yu Liu, Xingan Liu and Tianlai Li
Machines 2024, 12(4), 263; https://doi.org/10.3390/machines12040263 - 15 Apr 2024
Abstract
In this study, a novel cambered snow removal device is designed to achieve automatic snow removal in large curved areas, such as the south roof of a Chinese solar greenhouse. The theory of structural parameters and shear force is ambiguous. People are not
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In this study, a novel cambered snow removal device is designed to achieve automatic snow removal in large curved areas, such as the south roof of a Chinese solar greenhouse. The theory of structural parameters and shear force is ambiguous. People are not based on the greenhouse structure parameters for the selection of snow removal devices. Therefore, the quantitative relationship between the structure of the greenhouse span and the number of scissor arm-length knots is analysed, and the relationship between the material strength and application distance is determined. This study’s objectives are (1) to establish a theoretical model of scissor arm motion and (2) to analyse the force distribution of the scissor arm using multi-body dynamics. The results show that the scissor arm of a round-arch greenhouse has fewer sections but a larger arm length, whereas the scissor arm of a traditional solar greenhouse has more sections but a smaller arm length. Based on the shear force of the scissor structure, the optimised wall thickness reduces the force of the node by 17%.
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(This article belongs to the Section Machine Design and Theory)
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Open AccessArticle
Research on the Aerodynamic Performance and Collaborative Optimization Design of the Full-Scale Compact Inlet Chamber of a Nuclear-Powered Steam Turbine
by
Lei Zhang, Wei Jiang, Luotao Xie and Guobing Chen
Machines 2024, 12(4), 262; https://doi.org/10.3390/machines12040262 - 15 Apr 2024
Abstract
In nuclear-powered steam turbines, the aerodynamic performance of the inlet chamber tends to be contradictory to the compact design, which makes it difficult to achieve optimal efficiency and power in a nuclear-powered steam turbine. In this study, the quantitative correlation between compact design
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In nuclear-powered steam turbines, the aerodynamic performance of the inlet chamber tends to be contradictory to the compact design, which makes it difficult to achieve optimal efficiency and power in a nuclear-powered steam turbine. In this study, the quantitative correlation between compact design and aerodynamic performance was investigated to reveal the interaction mechanism between the aerodynamic performance of the inlet chamber of the steam turbine with its compactness. First, the effects of peripheral quantity and arrangement of inlets in the chamber inlet on its aerodynamic performance were studied. The results indicated that the proposed cross configuration exhibited optimized aerodynamic performance in multiple aspects. Then, the effects of two compactness indices (inlet/outlet area ratio and axial spacing at outlet) on the aerodynamic performance of the inlet chamber were investigated. The results indicated that the volume of the inlet chamber was proportional to the inlet/outlet area ratio, and an appropriate design of the inlet chamber can achieve compactness without significantly affecting its aerodynamic performance. In addition, the influencing mechanism of the compact optimization design on the aerodynamic performances of the inlet chamber was revealed. This study provides references for optimization designing an effective and compacted inlet chamber of steam turbines.
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(This article belongs to the Section Turbomachinery)
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