Machines

24 pages, 1860 KB

Open AccessArticle

Natural Motion Design for Energy-Efficient Pick-and-Place Scenarios

by Juan Pablo Mora, Carlos F. Rodriguez and Burkhard Corves

Machines 2026, 14(3), 330; https://doi.org/10.3390/machines14030330 (registering DOI) - 14 Mar 2026

Reducing the energy consumption of industrial robots performing pick-and-place tasks is required to increase profitability while reducing carbon footprint. Natural motion stands out as a mixed-energy-reduction strategy, especially useful for cyclical tasks. An optimization approach is proposed for calculating the elastic parameters, namely [...] Read more.

Reducing the energy consumption of industrial robots performing pick-and-place tasks is required to increase profitability while reducing carbon footprint. Natural motion stands out as a mixed-energy-reduction strategy, especially useful for cyclical tasks. An optimization approach is proposed for calculating the elastic parameters, namely the stiffness and equilibrium position, of constant-stiffness springs parallel to the actuators of parallel robots. Three typical trajectory-dependent methods for calculating these parameters are presented: free-vibration response, optimized, and predefined trajectory. As the set of springs and the task specification are strongly coupled, deviations from the nominal task would require replacing or removing the springs. Therefore, two adjustment strategies, one based on trajectory optimization and the other on equilibrium position update, are proposed to further exploit the natural motion. All optimization problems are solved and compared in a case study of a five-bar linkage performing a nominal pick-and-place task. Then, a palletizing pick-and-place scenario is introduced to perform the proposed trajectory and equilibrium adjustments. It is shown that using nominal springs reduces energy consumption near the nominal task, and implementing the proposed adjustments reduces energy over a wider region. Full article

(This article belongs to the Special Issue Selected Papers from the 8th International Symposium on Multibody Systems and Mechatronics)

37 pages, 10882 KB

Open AccessArticle

Predicting Part Orientation Distributions in Linear Feeders Using Simulation-Driven Deep Learning

by Idan Zucker and Chen Giladi

Machines 2026, 14(3), 329; https://doi.org/10.3390/machines14030329 - 13 Mar 2026

Abstract

Designing linear conveyor feeders with passive fences for automated part orientation remains largely trial and error because the final orientation distribution is difficult to predict reliably before physical testing. We present a simulation-driven deep learning pipeline that predicts the full distribution of final [...] Read more.

Designing linear conveyor feeders with passive fences for automated part orientation remains largely trial and error because the final orientation distribution is difficult to predict reliably before physical testing. We present a simulation-driven deep learning pipeline that predicts the full distribution of final in-plane orientations for extruded, z-axis-symmetric parts interacting with linear feeders containing up to two straight or curved fences. Using Bullet physics-based simulation in CoppeliaSim, we generate 1048 main part–feeder samples across 38 part geometries, plus 78 fence generalization and 110 unseen part samples for a total of 1236 (41 unique parts), and train regression networks and a Variational Autoencoder, or VAE, to predict 360-bin orientation probability distributions. On known parts, the regression model achieves high accuracy on held-out test configurations,

R^{2}

on circular CDFs

= 0.97 \pm 0.05

, and on unseen fence combinations,

R^{2}

on circular CDFs

= 0.89 \pm 0.11

. Generalization to previously unseen part geometries is more challenging, with

R^{2}

on circular CDFs

= 0.75 \pm 0.18

, indicating that geometric representation and dataset diversity are primary limitations. We also evaluate VAE reconstruction on datasets generated from simulations at different iteration counts: 5–100% of 1000 iterations in 5% increments. While within-level reconstruction remains high, cross-convergence evaluation shows that partial-iteration PMFs are far from fully converged labels in this dataset (overall CDF

R^{2}

= 0.01 at 5%, 0.32 at 50%, and 0.87 at 75%), so reduced-iteration simulations do not substitute for full convergence here. Overall, the proposed approach provides a data-driven foundation for feeder analysis and design, with future work focusing on improved geometric generalization and physical validation for industrial deployment. Full article

(This article belongs to the Topic Smart Product Design and Manufacturing on Industrial Internet)

12 pages, 3539 KB

Open AccessArticle

Cyclic Torsional Behavior of 3D-Printed ABS: Role of Infill Density and Raster Orientation

by Grayson Lumsden, Jeremy Sarpong and Khalil Khanafer

Machines 2026, 14(3), 328; https://doi.org/10.3390/machines14030328 - 13 Mar 2026

Abstract

This study investigates the fatigue behavior of 3D-printed ABS subjected to cyclic torsional loads, with a focus on the effects of infill density and raster angle on torsional fatigue performance. A total of 50 test specimens representing 25 unique combinations of infill density [...] Read more.

This study investigates the fatigue behavior of 3D-printed ABS subjected to cyclic torsional loads, with a focus on the effects of infill density and raster angle on torsional fatigue performance. A total of 50 test specimens representing 25 unique combinations of infill density (20%, 40%, 60%, 80%, 100%) and raster angle (25°/−65°, 45°/−45°, 75°/−15°, 0°/90°) were fabricated and tested using the cyclic torsion system. Fatigue failure was defined as a 75% reduction in torsional strength, recorded through cycle-by-cycle torque monitoring. The twist angle was cyclically varied between ±10° at a frequency of 5 Hz until failure occurred. The results indicate that increasing infill density significantly improves fatigue life by reducing internal porosity and enhancing load transfer, with the greatest gains observed at high infill levels (≥80%). Raster angle has a minimal effect at low infill densities but becomes critical at higher densities, where optimized filament orientations substantially extend fatigue life. Intermediate raster angles, particularly 25° and 75°, outperform orthogonal layouts by enabling better stress redistribution and inter-layer load sharing, while a 90° orientation leads to premature failure due to stress concentration and inter-layer debonding. When normalized by mass, specimens with 100% infill and intermediate raster angles achieve the highest fatigue endurance, highlighting the synergistic role of infill density and raster orientation in optimizing the durability and mass efficiency of 3D-printed components under cyclic torsional loading. Full article

(This article belongs to the Section Advanced Manufacturing)

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24 pages, 7825 KB

Open AccessArticle

A Novel Dynamic Surge Modeling Framework for Gas Turbines: Integration of Compressor Variable Geometry

by Jinshi Du, Yu Zhang, Miguel Martínez García and Adrian Spencer

Machines 2026, 14(3), 327; https://doi.org/10.3390/machines14030327 - 13 Mar 2026

Abstract

Gas turbines are complex mechatronic systems that require reliable dynamic models to support automated operation under varying aerodynamic conditions. This study presents a novel dynamic surge modeling framework that integrates compressor variable geometry into a gas turbine component-level model. A physics-based formulation is [...] Read more.

Gas turbines are complex mechatronic systems that require reliable dynamic models to support automated operation under varying aerodynamic conditions. This study presents a novel dynamic surge modeling framework that integrates compressor variable geometry into a gas turbine component-level model. A physics-based formulation is developed in which the influence of inlet guide vane (IGV) deflection is incorporated through sensitivity-based parameterization and a physics-informed extension of compressor performance characteristics. The proposed framework captures the nonlinear interaction between compressor surge dynamics and component-level system behavior, enabling consistent prediction of instability onset and dynamic stability margins over a wide range of operating conditions. Model verification through stability analysis, phase-space characterization, and time-domain simulations demonstrates that the framework reproduces key features of classical compressor surge and quantifies the impact of variable geometry on system stability. The results show that the proposed model provides a practical and computationally efficient basis for control-oriented surge analysis, including stability monitoring and surge delay assessment. By coupling the IGV-aware surge dynamics with a gas turbine component-level model, the proposed method enables control-oriented, automation-ready simulation for gas turbine design and control. Full article

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

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19 pages, 3599 KB

Open AccessArticle

Integrated Dynamic Modeling and Improved Deviation Coupling Control for Synchronous Motion of Multi-Joint Hydraulic Robotic Arms

by Longmei Zhao, Jianbo Dai, Haozhi Xu, Mingyuan Sun, Xiaoqi Li and Shuren Chen

Machines 2026, 14(3), 326; https://doi.org/10.3390/machines14030326 - 13 Mar 2026

Abstract

Multi-joint hydraulic robotic arms are core equipment in intelligent mining, yet their performance is often limited by strong dynamic coupling and nonlinear hydraulic effects. Traditional control methods struggle to achieve high-precision trajectory tracking and coordinated motion under high loads and flow-coupling constraints. To [...] Read more.

Multi-joint hydraulic robotic arms are core equipment in intelligent mining, yet their performance is often limited by strong dynamic coupling and nonlinear hydraulic effects. Traditional control methods struggle to achieve high-precision trajectory tracking and coordinated motion under high loads and flow-coupling constraints. To address these challenges, this paper establishes a coupled hydraulic–mechanical dynamic model for a multi-joint robotic arm. The mechanical dynamics are derived using the Lagrangian formulation, while the hydraulic dynamics account for flow coupling among cylinders. An improved deviation coupling control (IDCC) strategy is proposed, integrating feedforward–feedback compensation, coupling error regulation, and a flow-limiting correction term. Co-simulation in Simulink (2024b) and Amesim (2020) shows that under flow-saturation conditions, the improved strategy reduces the peak trajectory errors by approximately 47.88%, 28.08%, and 49.89% for Joints 1–3, respectively, and shortens the settling time by 27.93%. Experimental results from a three-joint hydraulic test platform confirm error reductions of 10.20–15.58% and a 31.50% decrease in overall adjustment time. The study demonstrates that the proposed control strategy effectively suppresses multi-joint coupling interferences, enhances trajectory tracking accuracy, and improves the adaptability of hydraulic robotic arms under flow-limited conditions, providing a viable solution for high-precision control in intelligent mining applications. Full article

(This article belongs to the Special Issue Design and Control of Compliant, Energy-Efficient Mechatronic and Robotic Systems)

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18 pages, 4115 KB

Open AccessArticle

The Design of a Bionic Frog Robot

by Zhengxian Song, Lan Yan and Feng Jiang

Machines 2026, 14(3), 325; https://doi.org/10.3390/machines14030325 - 13 Mar 2026

Abstract

This study developed a biomimetic jumping robot inspired by frogs to enhance its obstacle-crossing capabilities. The biological principles underlying the jumping biomechanics of frog hindlimbs were integrated into the robotic mechanism; quantitative analysis of the bionic structure and its jumping performance not only [...] Read more.

This study developed a biomimetic jumping robot inspired by frogs to enhance its obstacle-crossing capabilities. The biological principles underlying the jumping biomechanics of frog hindlimbs were integrated into the robotic mechanism; quantitative analysis of the bionic structure and its jumping performance not only provides mechanical engineering insights for investigating frog locomotion mechanics but also offers practical design references for the development of biomimetic mobile robots. Through theoretical calculations and application scenario analysis, a six-bar linkage mechanism was designed to simulate the force generation of frog hindlimbs, with tension springs mimicking the elastic energy storage function of the semimembranosus and gastrocnemius muscles. A reducer was integrated into the trunk to enable energy storage, and an adjustable single-hinge structure was adopted for the forelegs to realize take-off angle adjustment and shock absorption. Finite element simulations were conducted to validate the load-bearing capacity and strength of critical components. Multi-body dynamics and the particle swarm optimization (PSO) algorithm were employed to explore the relationship between input parameters and output performance metrics (jumping height and jumping distance), while orthogonal experimental analysis was used for comprehensive parameter evaluation. Finally, a physical prototype was fabricated, and its performance parameters were tested. The prototype has a mass of 150 g, generates a ground push force of 50 N, attains a jumping height of 380 mm, and achieves a maximum jumping distance of 500 mm. This study establishes a biologically inspired working principle for jumping robots and provides a novel practical prototype for research into biomimetic mobile robots. Full article

(This article belongs to the Special Issue Control and Mechanical System Engineering, 2nd Edition)

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12 pages, 1583 KB

Open AccessArticle

Dynamic Modal Evolution of High-Speed Train Car Bodies Under Complex Boundary and Load Conditions: A Field Test Study

by Zhanghui Xia, Baochen Liu and Dao Gong

Machines 2026, 14(3), 324; https://doi.org/10.3390/machines14030324 - 12 Mar 2026

Abstract

Stochastic Subspace Identification (SSI) theory offers the distinct advantage of extracting modal parameters directly from operational ambient excitations without requiring artificial force, ensuring completely true boundary conditions and providing extensive field measurement data. In this study, we systematically investigate the operational modal characteristics [...] Read more.

Stochastic Subspace Identification (SSI) theory offers the distinct advantage of extracting modal parameters directly from operational ambient excitations without requiring artificial force, ensuring completely true boundary conditions and providing extensive field measurement data. In this study, we systematically investigate the operational modal characteristics of Electric Multiple Units (EMUs) in the Chinese high-speed railway network under multi-dimensional coupling conditions, including wide speed ranges, axle load perturbations, air spring faults, and coupled operation. The results reveal that while car body modal frequencies remain largely insensitive to operating speed—indicating negligible effects of aerodynamic stiffness—they exhibit distinct sensitivities to mass and boundary variations. Specifically, an increase in axle load induces a significant attenuation (exceeding 5%) in low-order vertical bending frequencies, conforming to the dynamic mass law. Conversely, air spring deflation triggers a sharp increase in boundary stiffness, resulting in a 13.6% surge in torsional modal frequency, which serves as a critical indicator for fault diagnosis. Furthermore, coupled operation is found to primarily enhance system damping. Based on these findings, we establish a “condition-modal” vehicle sensitivity matrix, quantifying dynamic evolution mechanisms under complex boundaries and providing a vital baseline for monitoring the structural health of railway vehicles and conducting intelligent maintenance. Full article

(This article belongs to the Special Issue Research and Application of Rail Vehicle Technology)

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22 pages, 9366 KB

Open AccessArticle

A Super-Twisting Sliding Mode Robust Load Observer of PMSM for Electric Cylinder Considering Magnetic Saturation Effect

by Shengjie Fu, Qing Ai, Fengjun Shi, Tianliang Lin and Zhongshen Li

Machines 2026, 14(3), 323; https://doi.org/10.3390/machines14030323 - 12 Mar 2026

Abstract

The electric cylinder has become a research hotspot in the future because of its high energy efficiency and excellent dynamic performance. The electric cylinder is driven by a permanent magnet synchronous motor (PMSM). However, the existing high-performance control strategies of permanent magnet synchronous [...] Read more.

The electric cylinder has become a research hotspot in the future because of its high energy efficiency and excellent dynamic performance. The electric cylinder is driven by a permanent magnet synchronous motor (PMSM). However, the existing high-performance control strategies of permanent magnet synchronous motor, such as sliding mode variable structure control (SMC), model predictive control (MPC), and load torque feedforward, often face the challenge of unknown load torque when improving dynamic performance. The traditional load observation methods of PMSM involve the dq-axis inductance, which neglects the impact of inductance variation in interior PMSM (IPMSM) caused by the cross-coupling effect, flux weakening, or magnetic saturation effect. In this paper, a super-twisting sliding mode robust load observer (ST-RLO) is proposed, which performs load torque observation without reliance on inductance parameters. The feasibility and stability of the observer are analyzed theoretically. Experiments are carried out. The results show that compared with the conventional Luenberger load observer (CLLO) involving inductance, a better observation of the load torque is achieved by the ST-RLO, which has a better robustness for inductance variations and mismatching of inductance and inertia parameters. Full article

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

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43 pages, 2166 KB

Open AccessArticle

Research on Root Cause Analysis Method for Certain Civil Aircraft Based on Ensemble Learning and Large Language Model Reasoning

by Wenyou Du, Jingtao Du, Haoran Zhang and Dongsheng Yang

Machines 2026, 14(3), 322; https://doi.org/10.3390/machines14030322 - 12 Mar 2026

Abstract

To address the challenges commonly encountered in civil aircraft operating under multi-mode, strongly coupled closed-loop control—namely scarce fault samples, pronounced distribution shift, and root-cause explanations that are easily confounded by covariates—this paper proposes a root-cause analysis method that integrates ensemble learning with constraint-guided [...] Read more.

To address the challenges commonly encountered in civil aircraft operating under multi-mode, strongly coupled closed-loop control—namely scarce fault samples, pronounced distribution shift, and root-cause explanations that are easily confounded by covariates—this paper proposes a root-cause analysis method that integrates ensemble learning with constraint-guided reasoning by large language models (LLMs). First, for Full Authority Digital Engine Control (FADEC) monitoring sequences, a feature system comprising environment-normalized ratios, mechanism-informed mixing indices, and multi-scale temporal statistics is constructed, thereby improving cross-mode comparability and enhancing engineering-semantic expressiveness. Second, in the anomaly detection stage, a cost-sensitive LightGBM model is adopted and a validation-set-based adaptive thresholding strategy is introduced to achieve robust identification under highly imbalanced fault conditions. Furthermore, for Root Cause Analysis (RCA), a “computation–reasoning decoupling” framework is developed: Shapley Additive exPlanations (SHAP) are used to generate segment-level contribution evidence, while causal chains, engineering prohibitions, and structured output templates are injected into prompts to constrain the LLM, enabling it to infer root-cause candidates and produce structured explanations under mechanism-consistency constraints. Experiments on real flight data demonstrate that our method yields an anomaly detection F1-score of 0.9577 and improves overall RCA accuracy to 97.1% (versus 62.3% for a pure SHAP baseline). Practically, by translating complex high-dimensional data into actionable natural language diagnostic reports, the proposed method provides reliable and interpretable decision support for rapid RCA. Full article

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

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19 pages, 2389 KB

Open AccessArticle

Investigation on Dynamic and Transient Thermal Characteristics of High-Speed and High-Power-Density Dry Friction Clutch in STOVL Aircrafts

by Chu Zhu, Xiaokang Li, Dahuan Wei, Miao Pan, Hongzhi Yan and Yexin Xiao

Machines 2026, 14(3), 321; https://doi.org/10.3390/machines14030321 - 12 Mar 2026

Abstract

As a critical core component in the STOVL aircrafts, the dynamic and thermal performance of the aviation dry clutch directly determines the reliability of power transmission and the precision control, especially in high relative speed engagement and high power density conditions. Accordingly, this [...] Read more.

As a critical core component in the STOVL aircrafts, the dynamic and thermal performance of the aviation dry clutch directly determines the reliability of power transmission and the precision control, especially in high relative speed engagement and high power density conditions. Accordingly, this study proposes a 4-DOF dynamic model considering the time-varying of friction coefficient and nonlinear load characteristics, integrated with a transient thermal model incorporating the time-varying thermal parameters. The effects of pressure loading strategies and rotation speed on the dynamic and transient thermal responses are systematically analyzed. Furthermore, a novel temperature uniformity coefficient is developed to characterize the temperature field distribution. The results indicate that the pressure loading strategy fundamentally dictates the trade-off between engagement smoothness and thermal performance. Specifically, compared with other loading strategies, the linear loading strategy yields the most uniform thermal field (

U_{T z} = 0.4361

,

U_{T r} = 0.3971

) and the engagement smoothness (

J_{e r} = 2.353 \times 10^{5} {rad \cdot s}^{- 3}

) but increases sliding friction work (163.67 kJ). As rotation speed increases from 1500 r/min to 6000 r/min, the sliding friction work increases from 8.85 kJ to 163.67 kJ. Concurrently, the peak values of temperature, axial temperature gradient and axial temperature uniformity coefficient reach 116.557 °C, 80.622 °C and 0.4361, respectively. Consequently, an appropriate reduction in rotation speed combined with the adoption of linear loading strategy can not only facilitate the smoothness and friction loss reduction but also achieve a more uniform temperature distribution. These findings are not only essential for optimizing the thermal management and structural design of aviation dry clutches but also establish a quantitative basis for optimizing engagement strategies. Full article

(This article belongs to the Section Friction and Tribology)

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25 pages, 14486 KB

Open AccessArticle

A Policy Gradient-Based Improved KAN Convolutional Network Architecture for Fault Diagnosis of Aircraft Hydraulic Systems

by Jing Qu, Cunbao Ma and Zhiyu She

Machines 2026, 14(3), 320; https://doi.org/10.3390/machines14030320 - 12 Mar 2026

Abstract

As key power components in aviation machinery, airborne hydraulic systems exhibit significant coupling, nonlinearity, and strong noise interference, which pose enormous challenges for their mechanical fault diagnosis—an essential link in ensuring aviation mechanical system reliability. To address this issue, a policy gradient-based optimization [...] Read more.

As key power components in aviation machinery, airborne hydraulic systems exhibit significant coupling, nonlinearity, and strong noise interference, which pose enormous challenges for their mechanical fault diagnosis—an essential link in ensuring aviation mechanical system reliability. To address this issue, a policy gradient-based optimization method is proposed to autonomously tune network parameters, aiming to enhance the accuracy and robustness of mechanical fault diagnosis. Initially, a KAN (Kolmogorov–Arnold Network) convolution submodel is adopted to strengthen the extraction of weak mechanical fault features from complex hydraulic signals. Subsequently, the policy gradient methodology is employed to iteratively refine the overall network configuration, enabling adaptive optimization of fault diagnosis-related parameters. Extensive experiments on standard hydraulic system datasets demonstrate that the proposed approach outperforms other mainstream intelligent mechanical fault diagnosis methods in terms of diagnostic accuracy, anti-interference ability, and generalization performance. Full article

(This article belongs to the Special Issue Fault Diagnosis and Fault Tolerant Control in Mechanical System)

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20 pages, 11688 KB

Open AccessArticle

Development and Application of a Terminal Rigidity Enhancement Methodology for Parallel Robots

by Hanliang Fang, Jianxin Lin, Shuyi Ge, Yuzhe Nie, Jian Wang and Jun Zhang

Machines 2026, 14(3), 319; https://doi.org/10.3390/machines14030319 - 11 Mar 2026

Abstract

Parallel robots are recognized as a promising solution for heavy-load and high-efficiency tasks in modern manufacturing systems. The terminal rigidity is a critical performance metric for parallel robots, significantly affecting their payload capacity and machining accuracy. However, enhancing terminal rigidity is still a [...] Read more.

Parallel robots are recognized as a promising solution for heavy-load and high-efficiency tasks in modern manufacturing systems. The terminal rigidity is a critical performance metric for parallel robots, significantly affecting their payload capacity and machining accuracy. However, enhancing terminal rigidity is still a challenge due to the inherent design conflict between high rigidity and lightweight structures. Aiming at this challenge, this study proposes a practical yet high-ly efficient methodology to enhance terminal rigidity without incurring a weight increase. Firstly, an intensity factor is constructed as a discriminant metric to enable a sensitivity-based classification of components. Subsequently, a rigidity enhancement methodology is developed, which entails executing a step-by-step procedure to improve the stiffness of parallel robots. Next, the methodology is applied to a novel redundantly actuated parallel machining robot to demonstrate its practical utility in engineering design. The result shows that the proposed methodology achieves a 31.3% enhancement in linear terminal rigidity, coupled with a 5.6% decrease in overall weight. Finally, experimental verification is conducted through stiffness tests on a laboratory prototype, demonstrating that the enhanced terminal rigidity meets design expectations. Full article

(This article belongs to the Special Issue Design and Manufacture of Advanced Machines, Volume II)

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31 pages, 7238 KB

Open AccessArticle

Multimodal Fault Diagnosis of Rolling Bearings Based on GRU–ResNet–CBAM

by Kunbo Xu, Jingyang Zhang, Dongjun Liu, Chaoge Wang, Ran Wang and Funa Zhou

Machines 2026, 14(3), 318; https://doi.org/10.3390/machines14030318 - 11 Mar 2026

Abstract

Rolling bearings exhibit nonlinear and non-stationary fault signals under complex working conditions, rendering single-modal representation insufficient for accurate diagnosis. To address this limitation, this paper proposes a novel parallel multimodal fusion fault diagnosis model based on a Gated Recurrent Unit (GRU), a Residual [...] Read more.

Rolling bearings exhibit nonlinear and non-stationary fault signals under complex working conditions, rendering single-modal representation insufficient for accurate diagnosis. To address this limitation, this paper proposes a novel parallel multimodal fusion fault diagnosis model based on a Gated Recurrent Unit (GRU), a Residual Network (ResNet), and a Convolutional Block Attention Module (CBAM). First, a systematic multimodal representation selection framework is introduced, identifying the Markov Transition Field (MTF) as the optimal two-dimensional (2D) image modality due to its superior texture clarity and noise resistance compared to other methods. Second, parallel dual-branch architecture is designed to simultaneously process heterogeneous data. The 1D-GRU branch captures long-range temporal dependencies directly from raw vibration signals, while the 2D ResNet-CBAM branch extracts deep spatial features from the MTF images, adaptively focusing on key fault regions. These heterogeneous features are then fused through concatenation to retain complementary diagnostic information. Experimental validation on the Case Western Reserve University (CWRU) dataset demonstrates that the proposed model achieves a 99.57% accuracy in a 10-classification task. Furthermore, it exhibits significant parameter efficiency and outstanding robustness, with the accuracy decreasing by no more than 1.2% under noise interference and cross-load scenarios, comprehensively outperforming existing single-modal and advanced fusion methods. Full article

(This article belongs to the Special Issue Health Condition Monitoring, Intelligent Operation and Maintenance of Wind Turbines)

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17 pages, 3014 KB

Open AccessArticle

Development of a Megawatt Charging Capable Test Platform

by Orgun Güralp, Norman Bucknor and Madhusudan Raghavan

Machines 2026, 14(3), 317; https://doi.org/10.3390/machines14030317 - 11 Mar 2026

Abstract

Vehicle recharge time is a key barrier to widespread adoption of battery electric trucks, where megawatt class charging could be used to achieve refueling times comparable to internal combustion vehicles. This work presents the design and validation of a megawatt-capable rechargeable energy storage [...] Read more.

Vehicle recharge time is a key barrier to widespread adoption of battery electric trucks, where megawatt class charging could be used to achieve refueling times comparable to internal combustion vehicles. This work presents the design and validation of a megawatt-capable rechargeable energy storage system (144 kWh, 40P384S) together with a physics-based modeling framework for safe 1 MW operation. The pack architecture is reconfigurable, enabling nominal 750 V (80P192S) propulsion mode as well as 1125 V and 1500 V charging modes compatible with the Megawatt Charging System (MCS). An equivalent circuit model is developed to relate cell-level parameters to pack-level power, heat generation, and temperature rise, providing guidance on feasible charge profiles and thermal limits. A Simulink-based digital twin of the reconfigurable pack is then used to analyze sensitivity to current sensor mismatch and to verify protection logic for multiple bus voltage configurations. Finally, pack tests up to 1 MW confirm the model-predicted operating envelope and illustrate practical constraints imposed by charger voltage and pack resistance. The combined hardware and modeling approach provides a reusable platform for studying extreme fast charging of medium- and heavy-duty BEV packs-class charging -capable rechargeable energy storage system (144 kWh, 40P384S) together with a physics-based modeling framework for safe 1 MW operation. The pack architecture is reconfigurable, enabling nominal 750 V (80P192S) propulsion mode as well as 1125 V and 1500 V charging modes compatible with the Megawatt Charging System (MCS). An equivalent-circuit model is developed to relate cell-level parameters to pack-level power, heat generation, and temperature rise, providing guidance on feasible charge profiles and thermal limits. A Simulink-based digital twin of the reconfigurable pack is then used to analyze sensitivity to current–sensor mismatch and to verify protection logic for multiple bus-voltage configurations. Finally, pack tests up to 1 MW confirm the model-predicted operating envelope and illustrate practical constraints imposed by charger voltage and pack resistance. The combined hardware and modeling approach provides a reusable platform for studying extreme fast charging of medium- and heavy-duty BEV packs. Full article

(This article belongs to the Special Issue Selected Papers from MES-2025: Advances in Mechanical Engineering Solutions)

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27 pages, 1273 KB

Open AccessArticle

A Cooperative Iterated Greedy Algorithm for Multi-District Police Dispatching and Path Planning

by Panpan Xu, Jinfeng Wang and Xuan He

Machines 2026, 14(3), 316; https://doi.org/10.3390/machines14030316 - 10 Mar 2026

Abstract

Efficient cross-district police dispatching is vital for timely emergency response, yet it faces complex constraints involving coupled inter-district routing, task sequencing, escort capacities, and mandatory transfers at makeshift police posts. This study formulates the Multi-district Police Dispatching and Path Planning Problem (MDPDPP) with [...] Read more.

Efficient cross-district police dispatching is vital for timely emergency response, yet it faces complex constraints involving coupled inter-district routing, task sequencing, escort capacities, and mandatory transfers at makeshift police posts. This study formulates the Multi-district Police Dispatching and Path Planning Problem (MDPDPP) with makespan minimization. To address the problem’s hierarchical structure, we propose a Cooperative Iterated Greedy (CIG) algorithm. The problem is decomposed into district-level routing and capacity-constrained intra-district task scheduling, which are jointly optimized through a cooperative search mechanism. A capacity-aware decoding and local search strategy is further developed to capture the non-linear effects of escort capacity dynamics and mandatory detours. Computational experiments on a wide range of instances show that the proposed CIG algorithm consistently outperforms several state-of-the-art metaheuristics in terms of solution quality and robustness. Friedman statistical tests further confirm the statistical significance of the observed performance improvements, demonstrating the effectiveness of the proposed approach for complex multi-district police dispatching systems. Full article

(This article belongs to the Section Vehicle Engineering)

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22 pages, 4485 KB

Open AccessArticle

Design and Validation of a Real-Time FPGA-Based PID Control System for Angular Positioning in Servo-Hydraulic Actuators

by Ersin Tural and Rıza Emre Ergün

Machines 2026, 14(3), 315; https://doi.org/10.3390/machines14030315 - 10 Mar 2026

Abstract

Electro-hydraulic servo systems (EHSS) are widely used in industrial applications due to their high power-to-weight ratio; however, their nonlinear dynamics pose significant challenges for precise position control. This study proposes and validates a real-time Proportional–Integral–Derivative (PID) control system implemented on a Field Programmable [...] Read more.

Electro-hydraulic servo systems (EHSS) are widely used in industrial applications due to their high power-to-weight ratio; however, their nonlinear dynamics pose significant challenges for precise position control. This study proposes and validates a real-time Proportional–Integral–Derivative (PID) control system implemented on a Field Programmable Gate Array (FPGA) platform for the angular positioning of a servo-hydraulic actuator. The control algorithm is deployed on an embedded system to achieve high-speed execution independent of host processing. The controller gains were tuned using system identification techniques based on step response analysis. The system’s performance was experimentally assessed under both step inputs and sinusoidal trajectories. Experimental results demonstrated that the proposed controller achieved a rise time of 0.06 s and a steady-state error within ±1° for small step inputs. Furthermore, frequency domain analysis via Bode diagrams validated the system’s dynamic bandwidth, showing exceptional tracking capabilities at 10 Hz excitation with a negligible phase lag of −0.71°. These findings confirm that an FPGA-based PID control architecture effectively overcomes hydraulic nonlinearities, providing a robust and precise solution for real-time motion control compared to traditional methods. Full article

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

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25 pages, 7002 KB

Open AccessArticle

Experimental Investigation of a Pre-Engagement Spring-Steel Auxiliary Lining for Wear Reduction in Single-Plate Dry Clutch

by Aishwarya Dhoot, S. S. Bhavikatti and Sujit S. Pardeshi

Machines 2026, 14(3), 314; https://doi.org/10.3390/machines14030314 - 10 Mar 2026

Abstract

Premature wear and thermal degradation of friction linings can be significant limitations of conventional single-plate dry clutch systems under repeated engagement and high torque conditions. This study proposes a mechanically modified clutch incorporating an auxiliary spring-steel annular ring lining intended to promote staged [...] Read more.

Premature wear and thermal degradation of friction linings can be significant limitations of conventional single-plate dry clutch systems under repeated engagement and high torque conditions. This study proposes a mechanically modified clutch incorporating an auxiliary spring-steel annular ring lining intended to promote staged engagement and potential load sharing between two friction interfaces. Analytical torque capacity was estimated using uniform wear theory, and experimental validation was conducted on a laboratory clutch test rig under both continuous and cyclic engagement conditions. Mass loss, thickness reduction, surface temperature, and wear morphology were measured. Under the tested laboratory conditions, the modified clutch exhibited a 28–30% reduction in friction lining mass loss, approximately 6% reduction in thickness loss, and an estimated increase in service life of about 4.4 × 10⁷ revolutions (~7%) compared with a conventional clutch. Lower measured surface temperatures were also observed for the modified configuration, which may be associated with redistribution of frictional work. The results suggest that staged mechanical engagement through an auxiliary spring-steel ring lining can improve wear performance while retaining the basic architecture of a single-plate clutch without substantial change to overall dimensions. Full article

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

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29 pages, 18042 KB

Open AccessArticle

Design and Modelling of a Two-Axis Compliant Joint Based on Flexure Leaf Springs

by Kuncheng Feng, Hasiaoqier Han, Changzheng Chen, Jiaxin Li, Haifei Hu, Kai Zhang and Zhenbang Xu

Machines 2026, 14(3), 313; https://doi.org/10.3390/machines14030313 - 10 Mar 2026

Abstract

In the field of parallel robots, traditional rigid joints compromise motion accuracy owing to inherent friction and backlash, thus driving the demand for high-performance compliant joints. This paper proposes a parametric design method for a two-axis compliant joint that employs flexure leaf springs [...] Read more.

In the field of parallel robots, traditional rigid joints compromise motion accuracy owing to inherent friction and backlash, thus driving the demand for high-performance compliant joints. This paper proposes a parametric design method for a two-axis compliant joint that employs flexure leaf springs (FLSs) as rigid joint alternatives. The joint configuration consists of four FLSs arranged in a revolute–revolute (RR) layout. Based on Euler–Bernoulli beam theory and the deformation superposition principle, linear analytical models for the compliance and stress characteristics of both the flexure leaf spring (FLS) and the compliant joint are derived. These models are validated through finite element analysis (FEA) and rotational motion experiments. The results indicate that the relative errors between the analytical model (AM) and finite element model (FEM) are below 8%, while the relative errors between the AM and experimental data are within 12%. The proposed parametric design method enables rapid preliminary design and the performance evaluation of the two-axis compliant joint, which is intended as a rotational joint for six degrees of freedom (6-DOF) parallel robots with typical applications in high-precision optical alignment. Full article

(This article belongs to the Special Issue Towards Embodied Intelligence: Novel Kinematic Structures and AI-Guided Mechanism Design)

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23 pages, 6109 KB

Open AccessArticle

SLEC-Based Tunnel Lighting Design: A Sustainable Engineering Approach Through RSM

by Nazım İmal and Burak Öztürk

Machines 2026, 14(3), 312; https://doi.org/10.3390/machines14030312 - 10 Mar 2026

Abstract

Tunnel lighting systems serving pedestrian and vehicular traffic must simultaneously satisfy visual performance requirements and energy efficiency constraints. This study investigates the optimization of tunnel lighting design using a sustainable engineering approach based on Response Surface Methodology (RSM) and Specific Lighting Energy Consumption [...] Read more.

Tunnel lighting systems serving pedestrian and vehicular traffic must simultaneously satisfy visual performance requirements and energy efficiency constraints. This study investigates the optimization of tunnel lighting design using a sustainable engineering approach based on Response Surface Methodology (RSM) and Specific Lighting Energy Consumption (SLEC). Software-assisted lighting simulations were performed for two tunnel geometries—straight and double-curved—and horizontal (Eh) and vertical (Ev) illuminance levels were evaluated at five representative locations. The resulting data were used to construct RSM-based predictive models and to assess energy performance through SLEC. The effects of mounting height, luminaire spacing, luminous flux, number of luminaires, and tunnel type were systematically analyzed. The results demonstrate that luminaire spacing is the dominant parameter influencing illuminance levels and energy consumption. An optimal configuration consisting of a 12 m luminaire spacing, 5 m mounting height, and 10,000–12,000 lm luminous flux achieved a favorable balance between lighting quality and energy efficiency. Additionally, straight tunnels exhibited higher illuminance uniformity at shorter spacings, whereas curved tunnels showed improved performance under wider spacing conditions. The proposed RSM–SLEC framework provides a robust, data-driven methodology for sustainable tunnel lighting design without compromising safety or visual comfort. Full article

(This article belongs to the Special Issue Intelligent Propulsion Systems and Energy Control)

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