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A Review of Machine Learning-Based Thermal Error Modeling Methods for CNC Machine Tools
Vibration-Based Anomaly Detection in Industrial Machines: A Comparison of Autoencoders and Latent Spaces
Geometric Accuracy Design and Tolerance Allocation of Precision Horizontal Machining Centers
Marker-Based Safety Functionality for Human–Robot Collaboration Tasks by Means of Eye-Tracking Glasses

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) / CiteScore - Q1 (Control and Optimization)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.9 days after submission; acceptance to publication is undertaken in 2.4 days (median values for papers published in this journal in the first half of 2025).
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: 2.5 (2024); 5-Year Impact Factor: 2.6 (2024)

Imprint Information Journal Flyer Open Access ISSN: 2075-1702

Latest Articles

24 pages, 2683 KiB

Open AccessArticle

Zone-Wise Uncertainty Propagation and Dimensional Stability Assessment in CNC-Turned Components Using Manual and Automated Metrology Systems

by Mohammad S. Alsoufi, Saleh A. Bawazeer, Mohammed W. Alhazmi, Hani Alhazmi and Hasan H. Hijji

Machines 2025, 13(7), 585; https://doi.org/10.3390/machines13070585 (registering DOI) - 6 Jul 2025

Accurate measurement uncertainty quantification and its propagation are critical for dimensional compliance in precision manufacturing. This study presents a novel framework that examines the evolution of measurement error along the axial length of CNC-turned components, focusing on spatial and material-specific factors. A systematic [...] Read more.

Accurate measurement uncertainty quantification and its propagation are critical for dimensional compliance in precision manufacturing. This study presents a novel framework that examines the evolution of measurement error along the axial length of CNC-turned components, focusing on spatial and material-specific factors. A systematic experimental comparison was conducted between a manual Digital Vernier Caliper (DVC) and an automated Coordinate Measuring Machine (CMM) using five engineering materials: Aluminum Alloy 6061, Brass C26000, Bronze C51000, Carbon Steel 1020 Annealed, and Stainless Steel 304 Annealed. Dimensional measurements were taken from five consecutive machining zones to capture localized metrological behaviors. The results indicated that the CMM consistently achieved lower expanded uncertainty (as low as 0.00166 mm) and minimal propagated uncertainties (≤0.0038 mm), regardless of material hardness or cutting position. In contrast, the DVC demonstrated significantly higher uncertainty (up to 0.03333 mm) and propagated errors exceeding 0.035 mm, particularly in harder materials and unsupported zones affected by surface degradation and fixture variability. Root-sum-square (RSS) modeling confirmed that manual measurements are more prone to operator-induced error amplification. While the DVC sometimes recorded lower absolute errors, its substantial uncertainty margins hampered measurement reliability. To statistically validate these findings, a two-way ANOVA was performed, confirming that both the measurement system and machining zone significantly impacted uncertainty, as well as their interaction. These results emphasize the importance of material-informed and zone-sensitive metrology, highlighting the advantages of automated systems in sustaining measurement repeatability and dimensional stability in high-precision applications. Full article

(This article belongs to the Section Automation and Control Systems)

20 pages, 18025 KiB

Open AccessArticle

Numerical Research on Pressure Fluctuation Characteristics of Small-Scale and High-Speed Automotive Pump

by Lulu Zheng, Xiaoping Chen, Jinglei Qu and Xiaojie Ma

Machines 2025, 13(7), 584; https://doi.org/10.3390/machines13070584 (registering DOI) - 5 Jul 2025

Rotor–stator interaction and the coupling between the clearance flow and main flow amplify the flow complexity in small-scale, high-speed automotive pumps. This degrades the pressure fluctuations, compromising the operational stability of these pumps. To better understand the pressure fluctuation distribution characteristics within such [...] Read more.

Rotor–stator interaction and the coupling between the clearance flow and main flow amplify the flow complexity in small-scale, high-speed automotive pumps. This degrades the pressure fluctuations, compromising the operational stability of these pumps. To better understand the pressure fluctuation distribution characteristics within such a pump, the Reynolds-averaged Navier–Stokes equations and the shear stress transport k-ω turbulence model were applied to numerically compute the pump. The simulation results were compared with experimental data, and good agreement was achieved. The results show that pressure fluctuations in the main flow region are mainly dominated by the blade passing frequency, and the intensity of pressure fluctuations in the near-field area of the tongue reaches its peak value, showing significant fluctuation characteristics. Significant peak signals are captured in the low-frequency band of pressure fluctuations in the clearance region. The pressure fluctuation characteristics are also affected by the rotor–stator interaction between the impeller front shroud and the volute casing, while the dominant frequency is still the blade passing frequency. In addition, the dominant frequencies of pressure fluctuations in the main and clearance flows show a similar distribution to the flow rate, but the minimum amplitude corresponds to different flow rates. Full article

(This article belongs to the Section Turbomachinery)

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25 pages, 2069 KiB

Open AccessArticle

Remaining Useful Life Prediction of Aero-Engine Based on Improved GWO and 1DCNN

by Lihua Shen, Yucheng Wang, Baorui Du, Hailong Yang and He Fan

Machines 2025, 13(7), 583; https://doi.org/10.3390/machines13070583 (registering DOI) - 4 Jul 2025

With the deepening adoption of whole-lifecycle management paradigms in aviation equipment, accurate prediction of remaining useful life has emerged as a pivotal technical enabler for ensuring flight safety and optimizing maintenance resource allocation. This study systematically addresses limitations in existing data-driven remaining useful [...] Read more.

With the deepening adoption of whole-lifecycle management paradigms in aviation equipment, accurate prediction of remaining useful life has emerged as a pivotal technical enabler for ensuring flight safety and optimizing maintenance resource allocation. This study systematically addresses limitations in existing data-driven remaining useful life prediction methodologies through comprehensive optimizations spanning data preprocessing protocols and model architectural enhancements. To mitigate the local optimum entrapment inherent in deep learning hyperparameter optimization, an improved Gray Wolf Optimizer incorporating dynamic perturbation factors is proposed. This algorithm is subsequently deployed to optimize hyperparameters within the redesigned predictive architecture. Comparative analyses reveal that the proposed framework achieves superior prediction accuracy compared to mainstream optimization-driven models and state-of-the-art approaches. The results substantiate the capability of dynamic perturbation strategies to enhance both hyperparameter optimization quality and prediction stability, ultimately delivering an efficient solution for aero-engine remaining useful life estimation. The experiments on the C-MAPSS Dataset verify the effectiveness of these improvements. Full article

(This article belongs to the Section Machines Testing and Maintenance)

19 pages, 4219 KiB

Open AccessArticle

Schur Complement Optimized Iterative EKF for Visual–Inertial Odometry in Autonomous Vehicles

by Guo Ma, Cong Li, Hui Jing, Bing Kuang, Ming Li, Xiang Wang and Guangyu Jia

Machines 2025, 13(7), 582; https://doi.org/10.3390/machines13070582 (registering DOI) - 4 Jul 2025

Accuracy and nonlinear processing capabilities are critical to the positioning and navigation of autonomous vehicles in visual–inertial odometry (VIO). Existing filtering-based VIO methods struggle to deal with strongly nonlinear systems and often exhibit low precision. To this end, this paper proposes a VIO [...] Read more.

Accuracy and nonlinear processing capabilities are critical to the positioning and navigation of autonomous vehicles in visual–inertial odometry (VIO). Existing filtering-based VIO methods struggle to deal with strongly nonlinear systems and often exhibit low precision. To this end, this paper proposes a VIO method based on the Schur complement and Iterated Extended Kalman Filtering (IEKF). The algorithm first enhances ORB (Oriented FAST and Rotated BRIEF) features using Multi-Layer Perceptron (MLP) and Transformer architectures to improve feature robustness. It then integrates visual information and Inertial Measurement Unit (IMU) data through IEKF, constructing a complete residual model. The Schur complement is applied during covariance updates to compress the state dimension, improving computational efficiency and significantly enhancing the system’s ability to handle nonlinearities while maintaining real-time performance. Compared to traditional Extended Kalman Filtering (EKF), the proposed method demonstrates stronger stability and accuracy in high-dynamic scenarios. The experimental results show that the algorithm achieves superior state estimation performance on several typical visual–inertial datasets, demonstrating excellent accuracy and robustness. Full article

(This article belongs to the Topic Advances in Mobile Robotics Navigation, 2nd Volume)

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30 pages, 4475 KiB

Open AccessArticle

Hard Preloaded Duplex Ball Bearing Dynamic Model for Space Applications

by Pablo Riera, Luis Maria Macareno, Igor Fernandez de Bustos and Josu Aguirrebeitia

Machines 2025, 13(7), 581; https://doi.org/10.3390/machines13070581 (registering DOI) - 4 Jul 2025

Duplex ball bearings are common components in space satellite mechanisms, and their behaviour impacts the overall performance and reliability of these systems. During rocket launches, these bearings suffer high vibrational loads, making their dynamic response essential for their survival. To predict the dynamic [...] Read more.

Duplex ball bearings are common components in space satellite mechanisms, and their behaviour impacts the overall performance and reliability of these systems. During rocket launches, these bearings suffer high vibrational loads, making their dynamic response essential for their survival. To predict the dynamic behaviour under vibration, simulations and experimental tests are performed. However, published models for space applications fail to capture the variations observed in test responses. This study presents a multi-degree-of-freedom nonlinear multibody model of a hard-preloaded duplex space ball bearing, particularized for this work to the case in which the outer ring is attached to a shaker and the inner ring to a test dummy mass. The model incorporates the Hunt and Crossley contact damping formulation and employs quaternions to accurately represent rotational dynamics. The simulated model response is validated against previously published axial test data, and its response under step, sine, and random excitations is analysed both in the case of radial and axial excitation. The results reveal key insights into frequency evolution, stress distribution, gapping phenomena, and response amplification, providing a deeper understanding of the dynamic performance of space-grade ball bearings. Full article

(This article belongs to the Section Machine Design and Theory)

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23 pages, 11166 KiB

Open AccessArticle

Small-Signal Input Impedance Modeling of PWM Induction Motor Drives and Interactive Stability Assessment with DC Link

by Dirui Yang, Zhewen Kan, Yuewu Wang, Wenlong Ren, Yebin Yang and Kun Xia

Machines 2025, 13(7), 580; https://doi.org/10.3390/machines13070580 - 4 Jul 2025

DC link power supply systems that integrate power electronic converters are increasingly being adopted. In particular, emerging “source–load” systems, in which the DC link interfaces with converters, have attracted increasing research interest due to concerns about power quality and system stability. This paper [...] Read more.

DC link power supply systems that integrate power electronic converters are increasingly being adopted. In particular, emerging “source–load” systems, in which the DC link interfaces with converters, have attracted increasing research interest due to concerns about power quality and system stability. This paper addresses mid- and low-frequency oscillation issues in DC link voltage supplied induction motor drives (IMDs). It begins by constructing a multiple-input multiple-output (MIMO) state-space model of the induction motor. For the first time, the dq-axis control system is represented as an equivalent admittance model that forms two single-input single-output (SISO) loops. The PI controller and induction motor are integrated into the inverter’s input impedance model; Furthermore, the effectiveness and accuracy of the derived impedance model are experimentally validated under various operating conditions of the induction motor using a custom-built test platform. The experimental results offer a practical reference for system enhancement and stability evaluation. Full article

(This article belongs to the Special Issue Advanced Power Electronic Technologies in Electric Drive Systems, 2nd Edition)

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21 pages, 3327 KiB

Open AccessReview

Tread-Braked Wheels: Review and Recent Findings

by Gianluca Megna and Andrea Bracciali

Machines 2025, 13(7), 579; https://doi.org/10.3390/machines13070579 - 3 Jul 2025

Tread braking is still extensively used on freight wagons due to lower purchasing and maintenance costs compared to disk braking. Cast iron brake blocks were replaced by composite materials (organic or sintered) that result in a lower wheel roughness, reducing rolling noise. Unfortunately, [...] Read more.

Tread braking is still extensively used on freight wagons due to lower purchasing and maintenance costs compared to disk braking. Cast iron brake blocks were replaced by composite materials (organic or sintered) that result in a lower wheel roughness, reducing rolling noise. Unfortunately, composite brake blocks have a lower thermal conductivity, negatively affecting the wheel mechanical behavior as the braking energy is almost entirely dissipated by the wheels, which are therefore subjected to higher temperatures. Mechanical properties of the wheel material, such as yield stress and Rolling Contact Fatigue (RCF) behavior, markedly decrease with temperature, resulting in higher wear rates and wheel tread damage. Contacted to analyze defects not clearly defined in the current regulations used for maintenance and inspections, the authors surveyed the literature and the technical documentation about tread-braked wheels. The paper provides an updated view about the state-of-the-art of the research on thermomechanical behavior of railway wheels and discusses the implication of the increased thermal stresses generated by composite brake blocks. Full article

(This article belongs to the Special Issue Wheel–Rail Contact: Mechanics, Wear and Analysis)

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14 pages, 3542 KiB

Open AccessArticle

Study on Angular Velocity Measurement for Characterizing Viscous Resistance in a Ball Bearing

by Kyungmok Kim

Machines 2025, 13(7), 578; https://doi.org/10.3390/machines13070578 - 3 Jul 2025

This article describes a machine vision-based method for measuring the angular velocity of a rotating disk to characterize the viscous resistance of a ball bearing. A bright marker was attached to a disk connected to a shaft supported by two ball bearings. Rotation [...] Read more.

This article describes a machine vision-based method for measuring the angular velocity of a rotating disk to characterize the viscous resistance of a ball bearing. A bright marker was attached to a disk connected to a shaft supported by two ball bearings. Rotation of the marker was recorded with a digital camera. A simple algorithm was developed to track the trajectory of the marker and calculate angular displacement of the disk. For accurate detection of the rotating marker, the algorithm employed Multi-Otsu thresholding and the Least Squares Method (LSM). Verification of the proposed method was carried out through a direct comparison between the predicted rotational speeds and measured ones by a commercial tachometer. It was demonstrated that the percentage error of the proposed method was less than 1.75 percent. The evolution of angular velocity after motor power-off was measured and found to follow an exponential decay law. The exponent was found to remain consistent regardless of the induced rotational speed. This proposed measurement method will offer a simple and accurate non-contact solution for monitoring angular velocity and characterizing the resistance of a bearing. Full article

(This article belongs to the Special Issue Prognostics and Health Management and Structural Health Management in Mechanical and Manufacturing Systems)

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20 pages, 10723 KiB

Open AccessArticle

Influence of Different Mining Parameters on Collaborative Bearing Characteristics Between Hydraulic Supports and Surrounding Rock Coupling System

by Zhaosheng Meng, Jiacheng Wang, Xiaowan Lei and Penghui Xu

Machines 2025, 13(7), 577; https://doi.org/10.3390/machines13070577 - 3 Jul 2025

Hydraulic support (Hs) is an important support equipment in coal mining. With the continuous increase in coal mining intensity, stricter technical specifications have been put forward for the effectiveness of Hs. Hs is always in a dynamic coupling state with the surrounding rock. [...] Read more.

Hydraulic support (Hs) is an important support equipment in coal mining. With the continuous increase in coal mining intensity, stricter technical specifications have been put forward for the effectiveness of Hs. Hs is always in a dynamic coupling state with the surrounding rock. Investigating its dynamic adaptation characteristics in relation to surrounding rock is of great significance for improving its performance. In this work, a numerical analysis model of the ‘support–surrounding rock’ coupling system was established by taking the Hs (type ZZ 17000/33/72D) in the Kouzidong coal mine as an example and using explicit dynamic analysis software Ls-dyna R12. The dynamic response and pressure distribution characteristics of the hydraulic ‘support–surrounding rock’ coupling system under different mining heights and load conditions were investigated. The key vulnerable connection components of the Hs and their critical connection unit instability conditions were identified. These findings provide a theoretical basis for the structural optimization of four-column Hs, which will be beneficial in promoting the improvement of its load-bearing stability. Full article

(This article belongs to the Section Machine Design and Theory)

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25 pages, 8255 KiB

Open AccessArticle

A Practical Methodology for Accuracy and Quality Evaluation of Structured Light Systems in Automotive Inspection

by Antonio Lagudi, Umberto Severino, Loris Barbieri and Fabio Bruno

Machines 2025, 13(7), 576; https://doi.org/10.3390/machines13070576 - 2 Jul 2025

In the integration of structured light systems (SLSs) into automotive manufacturing pipelines, achieving reliable 3D reconstruction under industrial conditions remains a critical challenge. Factors such as environmental variability, surface reflectivity, and optical configuration often compromise dimensional accuracy and point cloud quality, limiting the [...] Read more.

In the integration of structured light systems (SLSs) into automotive manufacturing pipelines, achieving reliable 3D reconstruction under industrial conditions remains a critical challenge. Factors such as environmental variability, surface reflectivity, and optical configuration often compromise dimensional accuracy and point cloud quality, limiting the deployment of SLSs for inspection tasks. This paper presents a practical metric-based methodology for evaluating the dimensional accuracy and point cloud quality of SLSs targeted at automotive inspection applications. Unlike existing approaches focused primarily on theoretical or hardware-specific parameters, the proposed methodology considers all phases of the acquisition–reconstruction pipeline, including calibration, environmental variability, and image enhancement strategies, to practically guide engineers step-by-step in adapting SLSs to real-world operational constraints. The methodology was experimentally validated through a case study in an automotive production setting, where it enabled the detection of reconstruction biases caused by surface reflectivity and viewing angle. It also demonstrated the ability to quantify improvements obtained through image enhancement algorithms. These results confirm the methodology’s capacity to expose critical performance trade-offs and guide optimization choices in practical inspection scenarios. By offering a repeatable and application-oriented evaluation framework, the methodology supports the robust integration of digital vision systems in industrial workflows, facilitating more informed decisions for system designers, process engineers, and quality control professionals. Full article

(This article belongs to the Special Issue Digital Technologies to Support Human Factors Engineering in Manufacturing System Design: Theory and Applications)

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32 pages, 5640 KiB

Open AccessArticle

Computational Analysis of Aerodynamic Blade Load Transfer to the Powertrain of a Direct-Drive Multi-MW Wind Turbine

by Magnus Bichan, Pablo Jaen-Sola, Firdaus Muhammad-Sukki and Nazmi Sellami

Machines 2025, 13(7), 575; https://doi.org/10.3390/machines13070575 - 2 Jul 2025

This paper details the development of a full turbine model and ensuing aero-servo-elastic analysis of the International Energy Agency’s 15MW Reference Wind Turbine. This model provides the means to obtain realistic turbine performance data, of which normal and tangential blade loads are extracted [...] Read more.

This paper details the development of a full turbine model and ensuing aero-servo-elastic analysis of the International Energy Agency’s 15MW Reference Wind Turbine. This model provides the means to obtain realistic turbine performance data, of which normal and tangential blade loads are extracted and applied to a simplified drivetrain model developed expressly to quantify the shaft eccentricities caused by aerodynamic loading, thus determining the impact of aerodynamic loading on the generator structure. During this process, a method to determine main bearing stiffness values is presented, and values for the IEA-15MW-RWT obtained. It was found that wind speeds in the region of turbine cut-out induce shaft eccentricities as high as 56%, and that tangential loading has a significant contribution to shaft eccentricities, increasing deflection at the generator area by as much as 106% at high windspeeds, necessitating its inclusion. During a subsequent generator structure optimisation, the shaft eccentricities caused by the loading scenarios examined in this paper were found to increase the necessary mass of the rotor structure by 40%, to meet the reduced airgap clearance. Full article

(This article belongs to the Section Electrical Machines and Drives)

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19 pages, 2066 KiB

Open AccessArticle

TOPSIS-Based Methodology for Selecting Fused Filament Fabrication Machines

by Vignesh Venkat Raman, Rakshith Badarinath and Vittaldas V. Prabhu

Machines 2025, 13(7), 574; https://doi.org/10.3390/machines13070574 - 1 Jul 2025

Additive manufacturing (AM) has been gaining increased traction in the manufacturing industry due to its ability to fabricate prototypes and end use parts in low volumes at a much lower cost compared to conventional manufacturing processes. There has been research to select an [...] Read more.

Additive manufacturing (AM) has been gaining increased traction in the manufacturing industry due to its ability to fabricate prototypes and end use parts in low volumes at a much lower cost compared to conventional manufacturing processes. There has been research to select an AM process appropriate for fabricating particular parts. However, there is little extant research to select appropriate AM machines even though there is a growing number of AM machines with interesting topologies, structures, and systems. This paper proposes a methodology that aims to assist Technical Experts in selecting a machine for Fused Filament Fabrication (FFF). The methodology is built around a weighted Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which uses the concept of relative closeness and attribute weights to rank the machines. The paper uses Monte Carlo simulations for sensitivity analysis to evaluate the impact of randomizing attribute scoring, perturbing weights assigned, and probability distributions used to model human decision variability. The methodology and the sensitivity analysis were applied to three case studies, with five FFF machines and seven attributes, and top machines ranked for a specific part were found to be largely robust. Full article

(This article belongs to the Special Issue Recent Developments in Machine Design, Automation and Robotics)

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16 pages, 2954 KiB

Open AccessArticle

Design Technique on Speed Control Combined with an Inertial Element for Vibration Suppression

by Guoguang Zhang, Shuntai Xie, Peng Hou and Xiaoguang Wang

Machines 2025, 13(7), 573; https://doi.org/10.3390/machines13070573 - 1 Jul 2025

The suppression of mechanical resonance stands as the most crucial issue in enhancing system performance. In this study, based on a speed control system, the mechanisms of vibration suppression both with and without a first-order inertial element are analyzed and compared, and a [...] Read more.

The suppression of mechanical resonance stands as the most crucial issue in enhancing system performance. In this study, based on a speed control system, the mechanisms of vibration suppression both with and without a first-order inertial element are analyzed and compared, and a pole assignment method featuring an identical radius is put forward. Through an optimized design of pole assignment, the constraint conditions, control parameters, and applicable boundary of the first-order inertial element are explicitly derived in an analytical form. These derived results possess clear design significance and are very convenient for practical use. It is demonstrated that speed control with the first-order inertial element can effectively improve the underdamping performance. The proposed control method and the constrained optimization design of pole assignment are validated through experiments. Full article

(This article belongs to the Special Issue Mastering Vibrations: The Latest Breakthroughs in Control for Mechanical Systems)

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31 pages, 4195 KiB

Open AccessArticle

Designing Hybrid Mobility for Agricultural Robots: Performance Analysis of Wheeled and Tracked Systems in Variable Terrain

by Tong Wu, Dongyue Liu and Xiyun Li

Machines 2025, 13(7), 572; https://doi.org/10.3390/machines13070572 - 1 Jul 2025

This study investigates the operational performance of fruit-picking robots under varying terrain slopes and soil moisture conditions, with a focus on comparing wheeled and tracked locomotion systems. A modular robot platform was designed and tested in both controlled environments and actual mountainous orchards [...] Read more.

This study investigates the operational performance of fruit-picking robots under varying terrain slopes and soil moisture conditions, with a focus on comparing wheeled and tracked locomotion systems. A modular robot platform was designed and tested in both controlled environments and actual mountainous orchards in Shandong, China. The experiments assessed key performance metrics—average speed, slip rate, and path deviation—under combinations of four slope levels (0°, 8°, 18°, 28°) and three soil moisture levels (dry 10%, moderate 20%, wet 35%). Results reveal that wheeled robots perform optimally on dry and flat terrain but experience significant slippage and path deviation under steep and wet conditions. In contrast, tracked robots maintain better stability and terrain adaptability, demonstrating lower slip rates and more consistent trajectories across a wide range of conditions. A synergistic deterioration effect was observed when high slope and high soil moisture co-occur, significantly degrading the performance of wheeled systems, while tracked systems mitigated these effects. Complementary semi-structured interviews with 20 orchard stakeholders—including farmers, growers, and hired pickers—highlighted key user expectations: robust traction, terrain adaptability, reduced physical labor, and operational safety. The findings suggest that future agricultural robots should adopt adaptive hybrid mobility systems and integrate environmental perception capabilities to enhance performance in complex agricultural scenarios. These insights contribute practical and theoretical guidance for the design and deployment of intelligent fruit-picking robots in diverse field environments. Full article

(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)

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20 pages, 3470 KiB

Open AccessArticle

Hydrogen Supplementation in SI Engines: Enhancing Efficiency and Reducing Emissions with a Focus on Knock Phenomena

by Saugirdas Pukalskas, Alfredas Rimkus, Tadas Vipartas, Saulius Stravinskas, Donatas Kriaučiūnas, Gabrielius Mejeras and Andrius Ušinskas

Machines 2025, 13(7), 571; https://doi.org/10.3390/machines13070571 - 1 Jul 2025

This study investigates the impact of hydrogen supplementation on the performance, efficiency, and emissions of a spark-ignition internal combustion engine, with a specific focus on knock phenomena. A Nissan HR16DE engine was modified to operate in a dual-fuel mode using gasoline (E95) and [...] Read more.

This study investigates the impact of hydrogen supplementation on the performance, efficiency, and emissions of a spark-ignition internal combustion engine, with a specific focus on knock phenomena. A Nissan HR16DE engine was modified to operate in a dual-fuel mode using gasoline (E95) and high-purity hydrogen. Hydrogen was injected via secondary manifold injectors and managed through a reprogrammable MoTeC ECU, allowing precise control of ignition timing and fuel delivery. Experiments were conducted across various engine speeds and loads, with hydrogen mass fractions ranging from 0% to 30%. Results showed that increasing hydrogen content enhanced combustion intensity, thermal efficiency, and stability. Brake specific fuel consumption decreased by up to 43.4%, while brake thermal efficiency improved by 2–3%. CO, HC, and CO₂ emissions were significantly reduced. However, NO_x emissions increased with higher hydrogen concentrations due to elevated combustion temperatures. Knock tendency was effectively mitigated by retarding ignition timing, ensuring peak in-cylinder pressure occurred at 14–15° CAD aTDC. These findings demonstrate the potential of hydrogen supplementation to reduce fossil fuel use and greenhouse gas emissions in spark ignition engines, while highlighting the importance of precise combustion control to address challenges such as knock and NO_x formation. Full article

(This article belongs to the Special Issue Advanced Engine Energy Saving Technology)

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22 pages, 2415 KiB

Open AccessArticle

Ensemble Learning-Based Metamodel for Enhanced Surface Roughness Prediction in Polymeric Machining

by Elango Natarajan, Manickam Ramasamy, Sangeetha Elango, Karthikeyan Mohanraj, Chun Kit Ang and Ali Khalfallah

Machines 2025, 13(7), 570; https://doi.org/10.3390/machines13070570 - 1 Jul 2025

This paper proposes and demonstrates a domain-adapted ensemble machine learning approach for enhanced prediction of surface roughness (Ra) during the machining of polymeric materials. The proposed model methodology employs a two-stage pipelined architecture, where classified data are fed into the model for regressive [...] Read more.

This paper proposes and demonstrates a domain-adapted ensemble machine learning approach for enhanced prediction of surface roughness (Ra) during the machining of polymeric materials. The proposed model methodology employs a two-stage pipelined architecture, where classified data are fed into the model for regressive analysis. First, a classifier (Logistic Regression or XGBoost, selected based on performance) categorizes machining data into distinct regimes based on cutting Speed (Vc), feed rate (f), and depth of cut (ap) as inputs. This classification leverages output discretization to mitigate data imbalance and capture regime-specific patterns. Second, a regressor (Support Vector Regressor or XGBoost, selected based on performance) predicts Ra within each regime, utilizing the classifier’s output as an additional feature. This structured hybrid approach enables more robust prediction in small, noisy datasets characteristic of machining studies. To validate the methodology, experiments were conducted on Polyoxymethylene (POM), Polytetrafluoroethylene (PTFE), Polyether ether ketone (PEEK), and PEEK/MWCNT composite, using a L₂₇ Design of Experiments (DoEs) matrix. Model performance was optimized using k-fold cross-validation and hyperparameter tuning via grid search, with R-squared and RMSE as evaluation metrics. The resulting meta-model demonstrated high accuracy (R² > 90% for XGBoost regressor across all materials), significantly improving Ra prediction compared to single-model approaches. This enhanced predictive capability offers potential for optimizing machining processes and reducing material waste in polymer manufacturing. Full article

(This article belongs to the Special Issue Sustainable Manufacturing and Green Processing Methods, 2nd Edition)

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24 pages, 8171 KiB

Open AccessArticle

An Improved Adaptive Car-Following Model Based on the Unscented Kalman Filter for Vehicle Platoons’ Speed Control

by Caixia Huang, Wu Tang, Jiande Wang and Zhiyong Zhang

Machines 2025, 13(7), 569; https://doi.org/10.3390/machines13070569 - 1 Jul 2025

This study proposes an adaptive car-following model based on the unscented Kalman filter algorithm to enable coordinated speed control in vehicle platoons and to address key limitations present in conventional car-following models. Traditional models generally assume a fixed maximum speed within the optimal [...] Read more.

This study proposes an adaptive car-following model based on the unscented Kalman filter algorithm to enable coordinated speed control in vehicle platoons and to address key limitations present in conventional car-following models. Traditional models generally assume a fixed maximum speed within the optimal velocity function, which constrains effective platoon speed regulation across road segments with varying speed limits and lacks adaptability to dynamic scenarios such as changes in the platoon leader’s speed or substitution of the lead vehicle. The proposed adaptive model utilizes state estimation based on the unscented Kalman filter to dynamically identify each vehicle’s maximum achievable speed and to adjust inter-vehicle constraints, thereby enforcing a unified speed reference across the platoon. By estimating these maximum speeds and transmitting them to individual follower vehicles via vehicle-to-vehicle communication, the model promotes smooth acceleration and deceleration behavior, reduces headway variability, and mitigates shockwave propagation within the platoon. Simulation studies—covering both single-leader acceleration and intermittent acceleration scenarios—demonstrate that, compared with conventional car-following models, the adaptive model based on the unscented Kalman filter achieves superior speed synchronization, improved headway stability, and smoother acceleration transitions. These enhancements lead to substantial improvements in traffic flow efficiency and string stability. The proposed approach offers a practical solution for coordinated platoon speed control in intelligent transportation systems, with promising application prospects for real-world implementation. Full article

(This article belongs to the Special Issue Intelligent Control and Active Safety Techniques for Road Vehicles)

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30 pages, 18545 KiB

Open AccessArticle

Uniform Coverage Trajectory Planning for Polishing of Equation-Free Surfaces

by Linqiang Gong, Longxiang Li, Lei Zhang, Cheng Fan and Nianju Li

Machines 2025, 13(7), 568; https://doi.org/10.3390/machines13070568 - 30 Jun 2025

Conventional surface polishing trajectory generation relies on solving the plane trajectory equation in conjunction with the surface equation to obtain a surface polishing trajectory when the surface equation is known. However, in practical polishing processes, there exist equation-free surfaces which cannot be described [...] Read more.

Conventional surface polishing trajectory generation relies on solving the plane trajectory equation in conjunction with the surface equation to obtain a surface polishing trajectory when the surface equation is known. However, in practical polishing processes, there exist equation-free surfaces which cannot be described by equations and the generation of polishing trajectories on equation-free surfaces cannot be realized by an equation-solving strategy. In this paper, a polishing trajectory generation method for equation-free surfaces modeled by meshes based on the trajectory mapping strategy is proposed. As the calculation process for the coverage area of polishing trajectories requires invoking surface curvature information, this paper proposes a mesh surface curvature fitting algorithm. Regarding the problem of non-uniformity in the coverage area of polishing trajectories caused by surface curvature fluctuations, an algorithm for adjusting the position of polishing trajectory points on mesh surfaces is proposed, which enables the mapped trajectory points to be adjusted according to the required overlapping coverage area of the adjacent polishing trajectories. The uniform coverage of multiple polishing trajectories for rotationally symmetric workpieces is achieved by the proposed trajectory point position adjustment algorithm. Through experiment and analysis, it is verified that the proposed algorithm for uniform coverage of polishing trajectories can obtain better polishing results with the same polishing time. Full article

(This article belongs to the Topic Advanced Manufacturing and Surface Technology, 2nd Edition)

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20 pages, 2868 KiB

Open AccessArticle

Control Optimization of a Hybrid Magnetic Suspension Blood Pump Controller Based on the Finite Element Method

by Teng Jing, Yu Yang and Weimin Ru

Machines 2025, 13(7), 567; https://doi.org/10.3390/machines13070567 - 30 Jun 2025

This study focuses on a blood pump system equipped with four radial active magnetic bearings (RAMBs). The finite element method (FEM) was employed to optimize the physical parameters of the system. Based on this optimization, two intelligent PID tuning strategies—particle swarm optimization (PSO) [...] Read more.

This study focuses on a blood pump system equipped with four radial active magnetic bearings (RAMBs). The finite element method (FEM) was employed to optimize the physical parameters of the system. Based on this optimization, two intelligent PID tuning strategies—particle swarm optimization (PSO) and backpropagation (BP) neural networks—were compared. First, a differential control model of a single-degree-of-freedom active magnetic bearing was developed, based on the topology and operating principles of the radial magnetic bearings. Then, magnetic circuit parameters were precisely identified through finite element simulation, enabling accurate optimization of the physical model. To enhance control accuracy, intelligent tuning strategies based on PSO and BP neural networks were applied, effectively addressing the limitations of conventional PID controllers, which often rely on empirical tuning and lack precision. Finally, simulation experiments were conducted to evaluate the optimization performance of PSO and BP neural networks in the magnetic bearing control system. The results demonstrate that the improved PSO algorithm offers significant advantages over both the BP neural network and traditional manual PID tuning. Specifically, it achieved a rise time of 0.0049 s, a settling time of 0.0079 s, and a steady-state error of 0.0013 mm. The improved PSO algorithm ensures system stability while delivering faster dynamic response and superior control accuracy. Full article

(This article belongs to the Section Automation and Control Systems)

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26 pages, 6752 KiB

Open AccessArticle

A Q-Learning Crested Porcupine Optimizer for Adaptive UAV Path Planning

by Jiandong Liu, Yuejun He, Bing Shen, Jing Wang, Penggang Wang, Guoqing Zhang, Xiang Zhuang, Ran Chen and Wei Luo

Machines 2025, 13(7), 566; https://doi.org/10.3390/machines13070566 - 30 Jun 2025

Unmanned Aerial Vehicle (UAV) path planning is critical for ensuring flight safety and enhancing mission execution efficiency. This problem is typically formulated as a complex, multi-constrained, and nonlinear optimization task, often addressed using meta-heuristic algorithms. The Crested Porcupine Optimizer (CPO) has become an [...] Read more.

Unmanned Aerial Vehicle (UAV) path planning is critical for ensuring flight safety and enhancing mission execution efficiency. This problem is typically formulated as a complex, multi-constrained, and nonlinear optimization task, often addressed using meta-heuristic algorithms. The Crested Porcupine Optimizer (CPO) has become an excellent method to solve this problem; however, the standard CPO has limitations, such as the lack of adaptive parameter tuning to adapt to complex environments, slow convergence, and the tendency to fall into local optimal solutions. To address these issues, this paper proposes an algorithm named QCPO, which integrates CPO with Q-learning to improve UAV path optimization performance. Q-learning is employed to adaptively adjust the key parameters of the CPO, thereby overcoming the limitations of traditional fixed-parameter settings. Inspired by the porcupine’s defense mechanisms, a novel audiovisual coordination strategy is introduced to balance visual and auditory responses, accelerating convergence in the early optimization stages. A refined position update mechanism is designed to prevent excessive step sizes and boundary violations, enhancing the algorithm’s global search capability. A B-spline-based trajectory smoothing method is also incorporated to improve the feasibility and smoothness of the planned paths. In this paper, we compare QCPO with four outstanding heuristics, and QCPO achieves the lowest path cost in all three test scenarios, with path cost reductions of 30.23%, 26.41%, and 33.47%, respectively, compared to standard CPO. The experimental results confirm that QCPO offers an efficient and safe solution for UAV path planning. Full article

(This article belongs to the Special Issue Intelligent Control Techniques for Unmanned Aerial Vehicles)

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