Machines

22 pages, 1644 KB

Open AccessArticle

Vibration Signal-Based Fault Detection and Classification in Friction Stir Welding Process Using Statistical Features and Lazy Learning Classifiers

by Jegadeeshwaran Rakkiyannan, Balachandar Krishnamurthy, Lakshmi Pathi Jakkamputi, Sakthivel Gnanasekaran and Mohanraj Thangamuthu

Machines 2026, 14(7), 752; https://doi.org/10.3390/machines14070752 - 3 Jul 2026

Abstract

This paper proposes a vibration-based approach for real-time condition monitoring of Friction Stir Welding (FSW) tools, which are widely used in the marine and automotive industries. Conventional inspection techniques such as visual examination and endoscopy are not practicable during active welding operations. The [...] Read more.

This paper proposes a vibration-based approach for real-time condition monitoring of Friction Stir Welding (FSW) tools, which are widely used in the marine and automotive industries. Conventional inspection techniques such as visual examination and endoscopy are not practicable during active welding operations. The Locally Weighted Learning (LWL) algorithm, a lazy learning method, is used to address this limitation. Vibration signals are collected from a PLC-controlled FSW machine under five tool conditions, statistical features are extracted from the raw data, and a J48 decision tree is applied for feature selection to reduce computational overhead. Classification performance is evaluated using three lazy learning algorithms K-star (K*), LWL, and k-Nearest Neighbour (kNN) with LWL yielding the best result. The previously reported best accuracy for the same FSW setup was 73.16% at 1400 rpm using Random Forest; the proposed LWL-based approach achieves 92% accuracy under identical conditions, enabling earlier detection of tool faults before they result in weld defects or component failures. Full article

(This article belongs to the Special Issue Intelligent Predictive Maintenance and Machine Condition Monitoring)

35 pages, 12347 KB

Open AccessReview

A Review of Electric Machine Stator Winding Insulation Diagnostic Signal Processing Methods and Metrics

by Daniel Addae and Emmanuel Agamloh

Machines 2026, 14(7), 751; https://doi.org/10.3390/machines14070751 - 3 Jul 2026

Abstract

Stator winding insulation failure is a leading cause of electric machine failure. Early detection of winding insulation deterioration is essential to preventing catastrophic damage and ultimate electric machine failure. Various condition monitoring and diagnostic methods have been developed to assess insulation health while [...] Read more.

Stator winding insulation failure is a leading cause of electric machine failure. Early detection of winding insulation deterioration is essential to preventing catastrophic damage and ultimate electric machine failure. Various condition monitoring and diagnostic methods have been developed to assess insulation health while the machine is in operation. These diagnostic methods depend on different signal processing techniques that are used to extract insulation-sensitive information from measured signals. This paper presents a review of the diagnostic signal processing techniques that have been applied to stator winding insulation condition monitoring, spanning time-domain, frequency-domain, time–frequency-domain and data-driven approaches. Where appropriate, the underlying mathematical formulation of the reviewed technique is presented, the physical basis for its sensitivity to insulation condition monitoring is discussed, and the key strengths and limitations are identified. A comparative analysis with summary tables is provided to highlight the trade-offs between detection sensitivity, computational cost, hardware requirements and practical deployment considerations. The review shows that time- and frequency-domain methods are simple to implement, while time–frequency and data-driven methods generally offer higher performance, but require greater computation and validation. Also, the comparison shows that turn-to-turn and groundwall insulation monitoring have received more research attention, while phase-to-phase remains less developed. This review concludes by identifying the challenges and future research directions needed to advance this field from laboratory demonstrations toward industrial adoption. Full article

(This article belongs to the Special Issue Fault Diagnostics and Fault Tolerance of Synchronous Electric Drives, 2nd Edition)

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25 pages, 9749 KB

Open AccessArticle

An Integrated Path Planning Algorithm Based on Vector Jump Point Search and Ant Colony Optimization for Quay Crane Inspection

by Haoye Zhang, Zihan Lei, Mingxiao Wang, Zhipeng Hou, Hongren Zhao, Christophe Claramunt, Gang Tang and Weidong Zhu

Machines 2026, 14(7), 750; https://doi.org/10.3390/machines14070750 - 3 Jul 2026

Abstract

Unmanned aerial vehicles have become a promising platform for inspecting large port machinery; however, quay cranes contain sparse but complex steel-frame structures, multiple inspection points, and narrow collision-constrained spaces, which make efficient inspection path planning difficult. Existing approaches often focus either on global [...] Read more.

Unmanned aerial vehicles have become a promising platform for inspecting large port machinery; however, quay cranes contain sparse but complex steel-frame structures, multiple inspection points, and narrow collision-constrained spaces, which make efficient inspection path planning difficult. Existing approaches often focus either on global point sequencing or local collision-free search, and conventional global optimizers usually use straight-line distances that do not reflect obstacle-constrained flight costs. This paper proposes an integrated path planning method for quay crane inspection based on vector jump point search and ant colony optimization. In the local path-searching stage, vector-guided preprocessing and path simplification are used to calculate collision-free paths between mission points and construct a path cost matrix. In the global optimization stage, ant colony optimization determines the inspection sequence using the collision-free cost matrix rather than Euclidean distances. Simulation experiments were conducted on a simplified quay crane model of 132 m × 22 m × 70 m with 25 mission points. The results show that the proposed method reduced the average local path-searching time from 5.3392 s to 4.2907 s, corresponding to a 19.6% improvement over jump point search, while reducing the average local path length by 5.1%. The final global inspection path obtained in the experimental case was 516.1 m, which was shorter than those obtained by simulated annealing, genetic algorithm, particle swarm optimization, and the previous method. These results indicate that the proposed method can improve local planning efficiency and provide an effective inspection route for unmanned aerial vehicle-based quay crane inspection. Full article

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

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58 pages, 2345 KB

Open AccessReview

Overview of Thermal Management System for Hydrogen-Fueled Aero-Engines Driven by Energy Conservation and Digital Intelligence

by Yiqiao Li, Jing Huang, Yang Xiao, Shanlin Liu, Yifei Chen, Luyuan Gong, Yali Guo and Shengqiang Shen

Machines 2026, 14(7), 749; https://doi.org/10.3390/machines14070749 - 2 Jul 2026

Abstract

Under the background of the green transformation and energy conservation in the aviation field, hydrogen-fueled aero-engines are the primary direction for achieving sustainable aviation power development. However, the unique thermophysical properties of hydrogen fuel induce extreme thermal load challenges to engine thermal management. [...] Read more.

Under the background of the green transformation and energy conservation in the aviation field, hydrogen-fueled aero-engines are the primary direction for achieving sustainable aviation power development. However, the unique thermophysical properties of hydrogen fuel induce extreme thermal load challenges to engine thermal management. Based on the requirements of energy conservation and digital-intelligent technologies, this paper reviewed the recent research progress, important challenges, and future development directions in the thermal management field for hydrogen-fueled aero-engines, and filled the gaps in existing related reviews. (1) As for the liquid hydrogen thermal properties and thermal management requirements, the unique thermal physical properties of liquid hydrogen can easily cause fluctuations in heat load, large temperature differences, and material compatibility issues such as hydrogen embrittlement during storage, transportation, and combustion. The application of thermal barrier coatings, the design of targeted cooling structures, and the regulation of heat loss in the pipeline of the hydrogen supply system require particular attention. (2) As for the technical architecture and optimization of thermal management, the optimization of the high-pressure side manifolds in the cooled cooling air heat exchanger increases the flow uniformity by 18.8% and reduces the weight by 22.5%. The intercooled recuperated engine with the optimum area ratio reduces specific fuel consumption by 5.3% compared to the baseline engine in cruise. However, the system-level optimization research of the above widely recognized solutions is relatively limited in terms of coordinating the energy flow of engines. The baseline engine employed the method of system integration optimization to achieve a 2.99% increase in thrust and a 6.78% reduction in fuel consumption. (3) As for the thermal management modeling and simulation, the intelligent optimization method based on computational fluid dynamics reduces the pressure loss coefficient of the vane-integrated heat exchanger by 36%. Nevertheless, the multiphysics coupling model confronts a contradiction between computational cost and accuracy. (4) As for the comprehensive evaluation method, the advanced configuration of the hydrogen-fueled aero-engine can approximately reduce specific fuel consumption by 68.5% and NOx emission by 12.7% under the same maximum thrust condition. The hydrogen consumption of the proton exchange membrane fuel cells system model compared with the baseline system, optimized by the multi-objective optimization algorithm, has decreased by 15%, while the thermal uniformity has improved by 20–30%. However, the current evaluation system mostly focuses on a single dimension, lacking the analysis of nonlinear coupling among multiple factors and a closed-loop mechanism for evaluation, optimization, and verification. Future research should focus on the matching model of liquid hydrogen’s thermophysical properties and full flight conditions, global multi-energy flows optimization methods, multidimensional collaborative numerical simulation, multiphysics coupling models, and multidimensional comprehensive evaluation systems, to provide closed-loop theoretical support for the efficient, intelligent, and reliable thermal management system for hydrogen-fueled aero-engines. Full article

(This article belongs to the Special Issue Machine Tools for Precision Machining: Design, Control and Prospects)

32 pages, 3135 KB

Open AccessArticle

Higher-Order Kinematic Analysis of a Six-Bar Mechanism with a Prismatic Joint: Centrodes and Bresse Circles

by Eddie Gazo-Hanna, Ahmed Saber and Semaan Amine

Machines 2026, 14(7), 748; https://doi.org/10.3390/machines14070748 - 2 Jul 2026

Abstract

Planar linkage mechanisms remain a cornerstone of motion generation and trajectory control, yet the geometric tools that desRcribe their instantaneous behavior, namely centrodes and Bresse’s circles, have been developed almost exclusively for mechanisms with entirely revolute joints, where a sliding pair fundamentally alters [...] Read more.

Planar linkage mechanisms remain a cornerstone of motion generation and trajectory control, yet the geometric tools that desRcribe their instantaneous behavior, namely centrodes and Bresse’s circles, have been developed almost exclusively for mechanisms with entirely revolute joints, where a sliding pair fundamentally alters the velocity and acceleration fields and disrupts the symmetries on which classical curvature theory relies. This paper presents a comprehensive higher-order kinematic analysis of a planar six-link, single-degree-of-freedom mechanism in which a slider-crank stage and a rocker stage are coupled through a shared prismatic joint that acts simultaneously as output and input. Using vector algebra and a matrix-based loop-closure formulation, the position, velocity, and acceleration analyses are derived in closed form, yielding angular velocity ratios, the instantaneous centers of rotation and acceleration of both coupler links, and their inflection and stationarity circles. The analysis reveals a distinctive geometric constraint on the slider-side coupler’s instantaneous center, a decoupling of the curvature loci of the two couplers, and degenerate configurations, linked to coupler instantaneous-stop and rocker dead-point conditions, that arise at joint-invariant crank angles. Implemented as a computational algorithm and demonstrated on a carton flap-closing mechanism and cross-validated against independent multibody simulation, the framework confirms favorable transmission and dead-point clearance behavior, extending curvature-theory tools to linkages containing sliding pairs. Full article

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

35 pages, 1976 KB

Open AccessReview

Soft Robotics: Enabling Technologies, Applications, and Future Perspectives

by Yibo Wang, Mengwei Wu, Bintao Zou, Yimeng Du, Hengxu Du and Pengfei Chen

Machines 2026, 14(7), 747; https://doi.org/10.3390/machines14070747 - 2 Jul 2026

Abstract

Soft robots built from compliant materials and deformable structures are increasingly used in medical intervention, wearable assistance, delicate manipulation, and environmental exploration, where conventional rigid robots are limited by high mechanical impedance and poor morphological adaptability. However, their transition from laboratory prototypes to [...] Read more.

Soft robots built from compliant materials and deformable structures are increasingly used in medical intervention, wearable assistance, delicate manipulation, and environmental exploration, where conventional rigid robots are limited by high mechanical impedance and poor morphological adaptability. However, their transition from laboratory prototypes to deployable systems remains constrained by coupled bottlenecks in materials, actuation, sensing, modeling, control, energy supply, and manufacturing. This review summarizes recent advances in soft robotics through an evaluative framework covering actuation and materials, modeling and simulation, control strategies, multimodal sensing, and representative applications. Instead of treating these topics as independent descriptions, we compare the underlying mechanisms, measurable performance indicators, strengths, limitations, and application boundaries. Three conclusions emerge. First, no single actuation strategy can simultaneously maximize output force, response speed, energy efficiency, durability, miniaturization, and untethered operation. Second, high-fidelity continuum models improve physical accuracy but remain difficult to use for real-time control, whereas reduced-order and data-driven models improve efficiency at the cost of generalization, interpretability, or contact fidelity. Third, practical soft robots will depend on system-level integration of embedded sensing, physics-informed learning, robust control, reliable materials, and scalable fabrication. Future progress should therefore prioritize standardized benchmarks, lifecycle reliability, energy-autonomous operation, and task-specific comparisons with rigid robotic systems. Full article

(This article belongs to the Special Issue Innovations in Soft Robotics: Enhancing Safety, Performance, and Dexterity)

21 pages, 1791 KB

Open AccessArticle

Parametric Study of an H-Shaped-Core Magnetic Field Energy Harvester for Railway Traction-Returning Magnetic Fields

by Tingliang Zhao, Chengcheng Zuo, Zheng Jun Chew and Yang Kuang

Machines 2026, 14(7), 746; https://doi.org/10.3390/machines14070746 - 2 Jul 2026

Abstract

During train operation, railway traction-returning current generates a power-frequency magnetic field around the rail, offering a potential energy source for self-powered trackside monitoring nodes. The H-shaped-core magnetic field energy harvester (MFEH) is attractive because it can be installed beneath the rail without enclosing [...] Read more.

During train operation, railway traction-returning current generates a power-frequency magnetic field around the rail, offering a potential energy source for self-powered trackside monitoring nodes. The H-shaped-core magnetic field energy harvester (MFEH) is attractive because it can be installed beneath the rail without enclosing the conductor, yet its output is strongly affected by the coupled rail-core-coil system. To clarify these effects, a three-dimensional electromagnetic-circuit-coupled finite-element model of an experimentally validated laminated-silicon-steel H-shaped-core MFEH was established to examine core and coil parameters. Increasing the center-leg and side-leg lengths weakens demagnetization but intensifies eddy-current losses, causing output power to approach saturation. Under a 50 Hz, 300 A current in a 54E1 rail and series-tuned matching, output power approaches 5.1 W beyond a center-leg length of 1000 mm and 3.25 W beyond a side-leg length of 700 mm. Within the investigated ranges, center-leg and side-leg lengths of approximately 800 and 400 mm provide the best power–volume performance, respectively. Increasing side-leg height or width also improves output. A larger coil span improves output by reducing internal resistance, whereas more turns yield diminishing gains because of higher winding and eddy-current losses. These findings provide a quantitative basis for parametric design of H-shaped-core MFEHs in railway environments. Full article

(This article belongs to the Section Vehicle Engineering)

24 pages, 6940 KB

Open AccessArticle

A Rapid-Mode-Switching Small-Scale Crawling–Jumping Robot Based on a Dual-Clutch Mechanism

by Quan Liu, Beibei Dong, Mingge Li, Wenxi Zhang and Zhongjun Yin

Machines 2026, 14(7), 745; https://doi.org/10.3390/machines14070745 - 2 Jul 2026

Abstract

Conventional crawling–jumping robots often suffer from slow mode transitions and poor motion continuity, limiting their adaptability in complex environments. This paper presents a compact hybrid robot featuring a novel dual-clutch mechanism composed of an actively driven clutch and a passive clutch, enabling rapid, [...] Read more.

Conventional crawling–jumping robots often suffer from slow mode transitions and poor motion continuity, limiting their adaptability in complex environments. This paper presents a compact hybrid robot featuring a novel dual-clutch mechanism composed of an actively driven clutch and a passive clutch, enabling rapid, seamless transitions between crawling and jumping. The active clutch, driven by a single motor, controls elastic energy storage and release. In contrast, the passive clutch mechanically decouples the jumping and crawling modules during energy storage and enables automatic reset within 25 ms after takeoff. A dynamic jumping model and trajectory adjustment method are established, and analytical crossing criteria for trenches, obstacles, and platforms are derived. Experiments show that the robot achieves less than 3 s transition time from jumping to crawling, exhibits linearly controllable jumping height, and can actively regulate jump trajectories by independently adjusting crawling speed and takeoff velocity. The robot successfully traverses obstacles up to 2.7 times its body length. The proposed design provides an effective solution for rapid transitions between multimodal locomotion in small-scale robots. Full article

(This article belongs to the Special Issue Advances in Robot Kinematics and Dynamics: Innovations, Control Strategies, and Practical Applications)

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20 pages, 9321 KB

Open AccessArticle

Adaptive Load Balancing for Efficient Background Subtraction in Intelligent Transport Systems on Low-Cost Embedded Platforms

by Brahim Tebbaa, Mohamed Ragoubi, Lhoussain El Hajjami, Assia Arsalane, Abdessamad Klilou and Vidas Žuraulis

Machines 2026, 14(7), 744; https://doi.org/10.3390/machines14070744 - 2 Jul 2026

Abstract

Background subtraction (BS) is a fundamental technique in intelligent transport vision systems, widely used to detect and track moving objects, such as vehicles, pedestrians and obstacles, in driving environments. It plays a crucial role in advanced driver-assistance systems (ADAS) and autonomous driving by [...] Read more.

Background subtraction (BS) is a fundamental technique in intelligent transport vision systems, widely used to detect and track moving objects, such as vehicles, pedestrians and obstacles, in driving environments. It plays a crucial role in advanced driver-assistance systems (ADAS) and autonomous driving by enabling scene understanding and real-time motion analysis. However, BS processing must be optimized when targeting real-time processing on resource-constrained embedded systems, which present significant challenges due to limited computational power, memory constraints, and strict real-time requirements. Among the most commonly used BS techniques, the Codebook model and Gaussian Mixture Models (GMM) are known for their higher accuracy and light-model compared to many deep learning-based BS. In this work, we propose a fully heterogeneous CPU and GPU parallel implementation of both Codebook and GMM algorithms with an auto-load balancing over the processing units. This approach has been evaluated on the low-cost Jetson Orin Nano platform from NVIDIA, enabling efficient workload balancing across heterogeneous hardware resources. The suggested solution yields significant performance improvements over the state-of-the-art, achieving 59 frames per second (FPS) for GMM and 66 FPS for the Codebook method on full-HD (1080p) video streams. The results confirm the effectiveness of the proposed method in accelerating BS and demonstrate its suitability for real-time deployment in resource-constrained embedded environments. Full article

(This article belongs to the Special Issue Trends and Challenges in the Development and Operation of Modern Vehicles)

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15 pages, 4656 KB

Open AccessArticle

Torque Ripple Reduction and Power Density Improvement of a Slotless Motor Design for Rack-Type Electrical Power Steering

by Dong-Youn Shin, Do-Hyeon Choi, Hyung-Sub Han, Deepak Dubal and Won-Ho Kim

Machines 2026, 14(7), 743; https://doi.org/10.3390/machines14070743 - 2 Jul 2026

Abstract

Electric power steering (EPS) systems have become the dominant steering solution in modern vehicles due to their advantages in energy efficiency and driving convenience. Among EPS configurations, rack-type EPS(R-EPS) is widely adopted in mid-to-large vehicles for its direct and responsive steering characteristics. However, [...] Read more.

Electric power steering (EPS) systems have become the dominant steering solution in modern vehicles due to their advantages in energy efficiency and driving convenience. Among EPS configurations, rack-type EPS(R-EPS) is widely adopted in mid-to-large vehicles for its direct and responsive steering characteristics. However, conventional slotted motors used in R-EPS suffer from cogging torque and torque ripple caused by periodic reluctance variation in the stator tooth structure, resulting in vibration and noise directly perceived by the driver. This article proposes a slotless Surface Permanent Magnet Synchronous Motor (SPMSM) employing a Bar-Type magnet with a double-bridge rotor structure for R-EPS applications. By eliminating stator teeth, the proposed design achieves a uniform reluctance distribution during rotor rotation, theoretically reducing cogging torque to zero. The absence of stator tooth magnetic saturation further enables the use of high-remanence permanent magnets, improving gravimetric power density and enabling motor miniaturization. The proposed motor was designed and verified through finite element analysis (FEA). Compared to the conventional Arc-Type motor, the optimized design achieves a torque ripple reduction of 64.7% (from 5.07% to 1.79%) through Bar-Type magnet shaping combined with a 5 mm edge filet. The optimized design achieved an output power of 359.9 W, a gravimetric power density of 276.85 W/kg based on an active part weight of 1.30 kg, and a structural safety factor of 1146, demonstrating the effectiveness of the proposed double-bridge slotless motor for R-EPS applications. Full article

(This article belongs to the Topic Design and Control of Electrical Machines for Electric Vehicles)

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24 pages, 16900 KB

Open AccessArticle

The Design and Development of a Temperature Control System for Powder Sintering Processes in a Ceramic Sintering Machine

by Waldemar Samociuk

Machines 2026, 14(7), 742; https://doi.org/10.3390/machines14070742 - 1 Jul 2026

Abstract

This paper presents a control system for a powder sintering machine utilizing the alternating current (AC) sintering technique assisted by uniaxial compression. The AC flows simultaneously through both the sintered material and the die assembly. The procedural model of the control system and [...] Read more.

This paper presents a control system for a powder sintering machine utilizing the alternating current (AC) sintering technique assisted by uniaxial compression. The AC flows simultaneously through both the sintered material and the die assembly. The procedural model of the control system and its functionalities are described. Thermal models of the die assembly were developed using First-Order Plus Dead-Time (FOPDT) and Second-Order Plus Dead-Time (SOPDT) frameworks, followed by the synthesis of the control system. A prototype machine, developed at the University of Radom in cooperation with the University of Life Sciences in Lublin, is discussed, including its control algorithm and key process parameters affecting sample properties, established based on literature data. To achieve temperatures of 1700 °C and above, a specialized high-power supply (180 A, 400 VAC) with phase-angle and integral-cycle (group) control was implemented. The control system is based on a PLC equipped with temperature control loops, alongside measurements of shrinkage (displacement), compaction force, and auxiliary signals (vacuum and cooling systems). A dedicated control algorithm was developed to ensure process repeatability and optimization. For the ZrO₂-based composite analyzed in this manuscript, an FOPDT process model was determined, yielding an equivalent transport delay of approximately 83 s and an equivalent time constant of nearly 333 s. Based on this model, PID controller parameters were derived, and a time-profile program control algorithm was developed. Furthermore, based on literature data, selected mechanical properties of composites obtained via AC sintering are presented, which served as foundational design criteria for the developed machine. Full article

(This article belongs to the Special Issue Dimensional Measurement, Analysis, and Control for Precision Manufacturing)

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30 pages, 1239 KB

Open AccessArticle

A Dual-Stream Deep Reinforcement Learning Framework for Hot Rolling Production Scheduling

by Chi Wang, Wang Cao and Min Huang

Machines 2026, 14(7), 741; https://doi.org/10.3390/machines14070741 - 30 Jun 2026

Abstract

Hot Rolling Production Scheduling (HRPS) is a crucial combinatorial optimization problem characterized by severe conflicts between rigid physical rolling rules and strict order due dates. While real-time scheduling is essential for dynamic manufacturing, traditional meta-heuristics suffer from severe computational time bottlenecks. Conversely, standard [...] Read more.

Hot Rolling Production Scheduling (HRPS) is a crucial combinatorial optimization problem characterized by severe conflicts between rigid physical rolling rules and strict order due dates. While real-time scheduling is essential for dynamic manufacturing, traditional meta-heuristics suffer from severe computational time bottlenecks. Conversely, standard end-to-end Deep Reinforcement Learning (DRL) models offer rapid inference but typically struggle with spatio-temporal feature entanglement, training instability under extreme penalty landscapes, and poor zero-shot scale generalization. To bridge these gaps, this paper proposes a novel framework named Dual-Stream Group-Optimize Policy Optimization with Multiple Optima (DSGO-POMO). The framework introduces three core innovations: (1) a Dual-Stream intervention network that explicitly decouples and synergistically fuses physical attributes with temporal slacks; (2) a Group Relative Policy Optimization (GRPO) training mechanism to stabilize policy updates; and (3) an Entropy-Aware and Dual-Annealed Differential Active Search (EA-DAS) strategy to seamlessly adapt pre-trained weights to out-of-distribution scales. Extensive computational experiments validate the superiority of the proposed framework. On medium-scale instances ( Full article

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

23 pages, 5386 KB

Open AccessArticle

Effects of Uncertain Parameters on the Dynamic Response of a Wind Turbine Gearbox

by Bilel Karmi, Ahmed Guerine, Abdelkhalak El Hami, Slim Bouaziz, Abdelghani Saouab and Mohamed Haddar

Machines 2026, 14(7), 740; https://doi.org/10.3390/machines14070740 - 30 Jun 2026

Abstract

Producing reliable gear systems for wind turbines involves accounting for multiple uncertain parameters. To ensure operational vibrations remain controlled, it is essential to analyze the system’s sensitivity to these uncertainties. This study investigates the dynamic response of a two-stage wind turbine gear system, [...] Read more.

Producing reliable gear systems for wind turbines involves accounting for multiple uncertain parameters. To ensure operational vibrations remain controlled, it is essential to analyze the system’s sensitivity to these uncertainties. This study investigates the dynamic response of a two-stage wind turbine gear system, considering variations in many system variables. The goal is to evaluate the system’s reliability through bearing displacement analysis. A 12-DOF concentrated-parameter model is proposed to account for uncertainties in gear mass, damping, and the inertias of the pinion, gear, and input shaft. The dynamic response is examined using the Polynomial Chaos (PC) method across different orders and standard deviations, with results validated through the Monte Carlo (MC) method using 100,000 samples. Full article

(This article belongs to the Special Issue Advances in Dynamics and Vibration Control in Mechanical Engineering)

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34 pages, 4488 KB

Open AccessArticle

An Improved Frilled Lizard Optimizer for Integrating Distributed Generation, Capacitor Banks, and Reconfiguration in Radial Distribution Feeders

by Ali S. Aljumah, Mohammed H. Alqahtani, Ahmed R. Ginidi and Abdullah M. Shaheen

Machines 2026, 14(7), 739; https://doi.org/10.3390/machines14070739 - 30 Jun 2026

Abstract

For radial distribution systems (RDSs) to operate efficiently, reliably, and sustainably, distributed generation (DG), capacitor banks (CBs), and network reconfiguration (NR) must be optimally allocated and sized. The main objectives considered in this research are minimizing real power losses, improving voltage profiles, enhancing [...] Read more.

For radial distribution systems (RDSs) to operate efficiently, reliably, and sustainably, distributed generation (DG), capacitor banks (CBs), and network reconfiguration (NR) must be optimally allocated and sized. The main objectives considered in this research are minimizing real power losses, improving voltage profiles, enhancing energy utilization efficiency, and strengthening the operational reliability of distribution networks. To address this challenge, an Improved Frilled Lizard Optimizer (IFLO) is proposed to determine the optimal placement and sizing of DGs, CBs, and NR while satisfying system operational constraints. FLO is inspired by the adaptive survival and movement characteristics of frilled lizards in their natural ecosystem. The optimization mechanism of FLO is driven by hunting behavior for broad exploration and tree-climbing behavior for localized movement, enabling effective search and exploitation of promising regions. The IFLO introduces a defensive strategy phase, mimicking the lizard’s survival responses, and an adaptive local search phase, which models agile movement and stabilization behaviors. These enhancements improve the algorithm’s capability to reduce power losses, improve voltage regulation, increase network efficiency, and facilitate the effective integration of distributed energy resources into modern power distribution infrastructures. Comprehensive simulations on the IEEE 69-bus and the practical large-scale 141-bus RDS evaluate the impacts of DG and CB installation under practical operating constraints. This study investigates six scenarios involving different combinations of DG, CB, and NR to support efficient network planning and operation. Furthermore, recent optimization techniques, including Bezier Curve-Based Optimization (BCO), Horned Lizard Optimization Algorithm (HLOA), Whale Optimization Algorithm (WOA), Jaya Algorithm, and Particle Swarm Optimization (PSO), are implemented on the studied systems, and their results are compared with those of the proposed IFLO. The findings demonstrate that the suggested strategy outperforms existing optimization approaches in terms of convergence speed, solution quality, and network performance enhancement. The IFLO algorithm achieves an active power loss reduction of 92.69% for the large-scale system, while significantly improving voltage stability and operational efficiency. These outcomes contribute to the development of resilient, energy-efficient, and intelligent distribution infrastructures capable of supporting increased penetration of distributed energy resources under diverse operating conditions. Full article

(This article belongs to the Special Issue Sustainable Intelligent Design, Control and Optimization for Renewable-Integrated Power Systems)

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29 pages, 6556 KB

Open AccessArticle

Thermal Characteristics and Dynamic Behavior of Auxiliary Bearings in a Vertical Magnetic Suspension System

by Xiaoxu Pang, Chongfeng Jiang, Zhixin Shen, Dingkang Zhu, Aosha Wang and Kaili Wang

Machines 2026, 14(7), 738; https://doi.org/10.3390/machines14070738 - 30 Jun 2026

Abstract

Auxiliary bearings in vertical magnetic suspension systems can suffer thermal damage and impact-induced failure during rotor drop events caused by instability. This study aims to clarify the coupled effects of collision, frictional heating, and transient heat transfer on auxiliary bearing response. Dynamic, thermodynamic, [...] Read more.

Auxiliary bearings in vertical magnetic suspension systems can suffer thermal damage and impact-induced failure during rotor drop events caused by instability. This study aims to clarify the coupled effects of collision, frictional heating, and transient heat transfer on auxiliary bearing response. Dynamic, thermodynamic, and finite element models were established to analyze impact behavior, frictional heating, and temperature-field evolution, and were validated using rotor-drop measurements of impact force, rotor displacement, and outer-ring temperature together with post-test damage observations. The results show that severe impact and friction rapidly convert rotor kinetic energy into thermal energy, producing a non-uniform temperature field in the auxiliary bearings. The highest temperature occurs in the inner ring, followed by the rolling elements and outer ring, with peak temperatures of 169.59 °C, 154.66 °C, and 94.79 °C, respectively. Owing to gravity, gyroscopic motion, and rotor inclination during drop, the upper auxiliary bearing experiences greater impact loads, a faster speed increase, and a higher peak temperature rise than the lower bearing. Experimental evidence, including thermal discoloration, wear positions, and component damage, agrees with the simulated high-temperature regions. These results support thermal-shock-resistant design, structural optimization, and operational safety assessment of auxiliary bearings. Full article

(This article belongs to the Special Issue Tribology in Bearing Design for High-Speed and Energy-Efficient Mechanical Systems)

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23 pages, 4386 KB

Open AccessArticle

LIVE Digital Twin Using Integrated Modal and Transient Low-Fidelity Simulations for Condition Monitoring and Fault Diagnosis in Rotary Machines

by Seyyed Feisal Asbaghian Namin, Andrew E. Bondoc and Ahmad Barari

Machines 2026, 14(7), 737; https://doi.org/10.3390/machines14070737 - 30 Jun 2026

Abstract

The Digital Twin (DT) technology has emerged as one of the most prominent technologies for different applications including the machine condition monitoring, fault diagnosis, and predictive maintenance over the past decade. However, a major challenge in its widespread adoption is the development of [...] Read more.

The Digital Twin (DT) technology has emerged as one of the most prominent technologies for different applications including the machine condition monitoring, fault diagnosis, and predictive maintenance over the past decade. However, a major challenge in its widespread adoption is the development of comprehensive and generalized Digital Twin solutions. To address this, the LIVE Digital Twin framework has been introduced as a structural framework to develop and operate Digital Twins. LIVE stands for the main four stages of the framework: Learn, Identify, Verify, and Extend. A crucial aspect of LIVE Digital Twins is the integration of both Low-Fidelity (LF) and High-Fidelity (HF) simulations to manage various stages of Digital Twins’ life span. This paper uses the LIVE Digital Twin philosophy for predictive maintenance of rotary machines and focuses on the creation and application of an integrated dynamic Low-Fidelity simulation required as a main feature of this system. As part of this effort, a Simple Structural Dynamics (SSD) model was developed based on Finite Element Analysis (FEA) and Newmark’s time integration method. The Simple Structural Dynamics model was applied to a case study involving a rotary machine, where fundamental frequencies, mode shapes, and transient responses were analyzed for both healthy and faulty conditions. The results obtained using Simple Structural Dynamics were compared with those generated by a High-Fidelity simulation, demonstrating that Simple Structural Dynamics effectively predicts the system behavior while remaining computationally efficient enough to perform real-time simulations using the sensor data collected. The Simple Structural Dynamics proved to be computationally efficient, and it is highly scalable. Furthermore, the study thoroughly examined the impact of different defects, including cracks, unbalance, and bearing faults. Full article

(This article belongs to the Special Issue Advanced Machine Condition Monitoring and Fault Diagnosis)

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27 pages, 19105 KB

Open AccessArticle

PIV-Based Analysis of Internal Flow Evolution and Coherent Structures in a Semi-Open Axial Flow Fan

by Bin Li, Jun Wang, Qianhao Xiao and Yougen Huang

Machines 2026, 14(7), 736; https://doi.org/10.3390/machines14070736 - 30 Jun 2026

Abstract

The internal flow of a semi-open axial flow fan is highly three-dimensional and unsteady due to the absence of a confined passage. The evolution of complex vortical structures, such as the tip leakage vortex (TLV) and corner separation vortex (CSV), remains poorly understood. [...] Read more.

The internal flow of a semi-open axial flow fan is highly three-dimensional and unsteady due to the absence of a confined passage. The evolution of complex vortical structures, such as the tip leakage vortex (TLV) and corner separation vortex (CSV), remains poorly understood. This study used high-resolution particle image velocimetry (PIV) to conduct multi-region, multi-view measurements of the flow field in a semi-open fan for an outdoor air conditioning unit. The generation, development, and breakdown of the TLV were analyzed, revealing transient nonuniform flow and wake evolution. Dynamic mode decomposition (DMD) was applied to extract dominant frequencies and spatial modes. The results show that the TLV has a dominant frequency of 98.5 Hz (2.19 times the rotational frequency), accounting for 88.5% of the total energy, and exhibits periodic shedding and asymmetric breakdown. The CSV dominates at 16.44 Hz, slightly above blade rotation, and interacts with the TLV. In the wake region, the dominant frequency is 248.45 Hz, arising from the nonlinear superposition of TLV harmonics, the CSV frequency, and the blade passing frequency. This study provides an experimental basis and a low-dimensional coherent structure model for internal flow diagnostics and the structural optimization of semi-open axial flow fans. Full article

(This article belongs to the Special Issue Advanced Research and Development in Fluid Machinery: Design, Optimization, and Applications)

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24 pages, 2395 KB

Open AccessArticle

Effect of Inter-Turn Short Circuit Faults on Axial Flux Synchronous Reluctance Motor Performance

by Mustafa Eker, Emrah Eser and Mehmet Akar

Machines 2026, 14(7), 735; https://doi.org/10.3390/machines14070735 - 29 Jun 2026

Abstract

In this study, the effects of stator winding inter-turn short-circuit faults occurring in an Axial Flux Synchronous Reluctance Motor (AF-SynRM) on motor performance were experimentally investigated. Within the scope of the study, a total of 12 different fault scenarios were created using different [...] Read more.

In this study, the effects of stator winding inter-turn short-circuit faults occurring in an Axial Flux Synchronous Reluctance Motor (AF-SynRM) on motor performance were experimentally investigated. Within the scope of the study, a total of 12 different fault scenarios were created using different fault ratios and fault resistances, and the experiments were carried out under 4 different speed conditions and 5 different load conditions. In the analyses, phase current, fault current, power factor, and MTPA angle behaviors were evaluated. The obtained results demonstrated that significant increases in motor currents occurred particularly under low fault resistance and high load conditions. In addition, it was determined that the faults caused variations in power factor characteristic, while the MTPA angle, which represents the optimum operating point of the motor, shifted depending on the fault severity. Overall, the results revealed that stator winding inter-turn short-circuit faults (SITF) affect not only current levels but also energy conversion performance and control characteristics of the motor. As the first study in the literature to experimentally investigate the effects of SITF in an AF-SynRM structure within this scope, it is considered that the findings obtained will provide significant contributions to fault analysis and fault-tolerant drive systems. Full article

(This article belongs to the Topic Advanced Electrical Machines and Drives Technologies, 3rd Edition)

29 pages, 21577 KB

Open AccessArticle

Stochastic Response Analysis of the Maglev Vehicle–Bridge Coupled System Considering Uncertain Parameters

by Shanqiang Fu, Bangtai Pan, Leibin Wen and Kai Zhou

Machines 2026, 14(7), 734; https://doi.org/10.3390/machines14070734 - 29 Jun 2026

Abstract

Previous studies on maglev vehicle–bridge coupled systems have mostly described the bridge using classical boundary conditions, while the effects of general constrained boundaries and uncertain parameters have not been fully considered. In this study, an energy-based dynamic model of a maglev vehicle–bridge coupled [...] Read more.

Previous studies on maglev vehicle–bridge coupled systems have mostly described the bridge using classical boundary conditions, while the effects of general constrained boundaries and uncertain parameters have not been fully considered. In this study, an energy-based dynamic model of a maglev vehicle–bridge coupled system is established. The boundary constraints of the bridge are introduced through equivalent springs, so that complex boundary conditions can be represented in a unified form. The proposed model is verified by comparison with published results. On this basis, Monte Carlo simulations are carried out to investigate the effects of random suspension parameters and random control parameters on the dynamic responses of the system. Two simplified electromagnetic-force models are also considered, and Sobol sensitivity analysis is used to evaluate the contributions of different parameters to the vibration responses and vibration energy. The results indicate that the suspension and control parameters affect different response quantities in different ways. The two electromagnetic-force models also lead to different sensitivity results, especially when the vibration energy is used as the evaluation index. The proposed method provides a useful tool for analyzing the stochastic vibration mechanism and optimizing the parameters of maglev vehicle–bridge coupled systems under general constrained boundaries. Full article

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

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