Machines

31 pages, 5073 KB

Open AccessArticle

Improvement in DFIG-Based Wind Energy Conversion System LVRT Capability in Compliance with Algerian Grid Code

by Brahim Djidel, Lakhdar Mokrani, Abdellah Kouzou, Mohamed Machmoum, Jose Rodriguez and Mohamed Abdelrahem

Machines 2026, 14(1), 22; https://doi.org/10.3390/machines14010022 - 23 Dec 2025

Abstract

During voltage dips, wind turbines must remain connected to the electrical grid and contribute to voltage stabilization. This study analyzes the impact of voltage dips arising from grid faults on Doubly Fed Induction Generator (DFIG) based Wind Energy Conversion Systems (WECSs). This paper [...] Read more.

During voltage dips, wind turbines must remain connected to the electrical grid and contribute to voltage stabilization. This study analyzes the impact of voltage dips arising from grid faults on Doubly Fed Induction Generator (DFIG) based Wind Energy Conversion Systems (WECSs). This paper presents a review of the technical regulations for integrating the Algerian electricity grid with the Low Voltage Ride Through (LVRT) system, along with specific requirements for renewable power generation installations. Additionally, the modeling and control strategy of DFIG based WECS has been outlined. Voltage dips can induce excessive currents that threaten the DFIG rotor and may cause harmful peak oscillations in the DC-link voltage, and can lead to turbine speed increase due to the sudden imbalance between the mechanical input torque and the reduced electromagnetic torque. To counter this, a modified vector control and crowbar protection mechanism were integrated. Its role is to mitigate these risks, thereby ensuring the system remains stable and operational through grid faults. The proposed system successfully meets the stringent Algerian LVRT requirements, with voltage dipping to zero for 0.3 s and recovering gradually. Simulations confirm that rotor and stator currents remain within safe limits (peak rotor current at 0.93

p u

, and peak stator current at 1.36

p u

). The DC-link voltage, despite a transient rise due to the continued power conversion from the rotor-side converter during the grid fault, was effectively stabilized and maintained within safe operating margins (with less than 14% overshoot). This stability was achieved as the crowbar ensured power balance by managing active and reactive power. Notably, the turbine rotor speed demonstrated stability, peaking at 1.28

p u

within mechanical limits. Full article

(This article belongs to the Special Issue Advances in Power Electronics for Electromechanical Energy Conversion and Drive Systems)

24 pages, 5595 KB

Open AccessArticle

Online End Deformation Calculation Method for Mill Relining Manipulator Based on Structural Decomposition and Kolmogorov-Arnold Network

by Mingyuan Wang, Yujun Xue, Jishun Li, Shuai Li and Yunhua Bai

Machines 2026, 14(1), 21; https://doi.org/10.3390/machines14010021 - 23 Dec 2025

Abstract

Due to the large mass, high end load, and long action distance of a mill relining manipulator, gravity effects inevitably lead to a reduction in end effector positioning accuracy. To solve this problem, an online calculation method is proposed to realize real-time end [...] Read more.

Due to the large mass, high end load, and long action distance of a mill relining manipulator, gravity effects inevitably lead to a reduction in end effector positioning accuracy. To solve this problem, an online calculation method is proposed to realize real-time end effector deformation prediction. First, a manipulator is simplified into two cantilever beams: the upper arm and the forearm. Second, a reaction force and moment transformation model is established based on the coupling relationship between the forearm and upper arm. Third, finite element (FE) static analysis and simulation are carried out to obtain the end deformation. A total of 3528 discrete joint configurations are selected to cover the entire joint space, and their corresponding FE solutions are used to establish the end deformation offline dataset. Finally, an online deformation calculation algorithm based on Kolmogorov–Arnold networks (KANs) is developed to predict end deformation in any working condition. Visualization analysis and validation experiments are conducted and demonstrate the superiority of the proposed method in reducing gravity effects and improving computational efficiency. In summary, the proposed method provides support for end position compensation, especially for heavy-duty manipulators. Full article

(This article belongs to the Special Issue The Kinematics and Dynamics of Mechanisms and Robots)

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27 pages, 3196 KB

Open AccessArticle

Reliability-Based Robust Design Optimization Using Data-Driven Polynomial Chaos Expansion

by Zhaowang Li, Zhaozhan Li, Jufang Jia and Xiangdong He

Machines 2026, 14(1), 20; https://doi.org/10.3390/machines14010020 - 23 Dec 2025

Abstract

As the complexity of modern engineering systems continues to increase, traditional reliability analysis methods still face challenges regarding computational efficiency and reliability in scenarios where the distribution information of random variables is incomplete and samples are sparse. Therefore, this study develops a data-driven [...] Read more.

As the complexity of modern engineering systems continues to increase, traditional reliability analysis methods still face challenges regarding computational efficiency and reliability in scenarios where the distribution information of random variables is incomplete and samples are sparse. Therefore, this study develops a data-driven polynomial chaos expansion (DD-PCE) model for scenarios with limited samples and applies it to reliability-based robust design optimization (RBRDO). The model directly constructs orthogonal polynomial basis functions from input data by matching statistical moments, thereby avoiding the need for original data or complete statistical information as required by traditional PCE methods. To address the statistical moment estimation bias caused by sparse samples, kernel density estimation (KDE) is employed to augment the data derived from limited samples. Furthermore, to enhance computational efficiency, after determining the DD-PCE coefficients, the first four moments of the DD-PCE are obtained analytically, and reliability is computed based on the maximum entropy principle (MEP), thereby eliminating the additional step of solving reliability as required by traditional PCE methods. The proposed approach is validated through a mechanical structure and five mathematical functions, with RBRDO studies conducted on three typical structures and one practical engineering case. The results demonstrate that, while ensuring computational accuracy, this method saves approximately 90% of the time compared to the Monte Carlo simulation (MCS) method, significantly improving computational efficiency. Full article

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

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51 pages, 16272 KB

Open AccessReview

A Review on In-Situ Monitoring in Wire Arc Additive Manufacturing: Technologies, Applications, Challenges, and Needs

by Mohammad Arjomandi, Jackson Motley, Quang Ngo, Yoosuf Anees, Muhammad Ayaan Afzal and Tuhin Mukherjee

Machines 2026, 14(1), 19; https://doi.org/10.3390/machines14010019 - 22 Dec 2025

Abstract

Wire Arc Additive Manufacturing (WAAM), also known as Wire Arc Directed Energy Deposition, is used for fabricating large metallic components with high deposition rates. However, the process often leads to residual stress, distortion, defects, undesirable microstructure, and inconsistent bead geometry. These challenges necessitate [...] Read more.

Wire Arc Additive Manufacturing (WAAM), also known as Wire Arc Directed Energy Deposition, is used for fabricating large metallic components with high deposition rates. However, the process often leads to residual stress, distortion, defects, undesirable microstructure, and inconsistent bead geometry. These challenges necessitate reliable in-situ monitoring for process understanding, quality assurance, and control. While several reviews exist on in-situ monitoring in other additive manufacturing processes, systematic coverage of sensing methods specifically tailored for WAAM remains limited. This review fills that gap by providing a comprehensive analysis of existing in-situ monitoring approaches in WAAM, including thermal, optical, acoustic, electrical, force, and geometric sensing. It compares the relative maturity and applicability of each technique, highlights the challenges posed by arc light, spatter, and large melt pool dynamics, and discusses recent advances in real-time defect detection and control, process monitoring, microstructure and property prediction, and minimization of residual stress and distortion. Apart from providing a synthesis of the existing literature, the review also provides research needs, including the standardization of monitoring methodologies, the development of scalable sensing systems, integration of advanced AI-driven data analytics, coupling of real-time monitoring with multi-physics modeling, exploration of quantum sensing, and the transition of current research from laboratory demonstrations to industrial-scale WAAM implementation. Full article

(This article belongs to the Special Issue In Situ Monitoring of Manufacturing Processes)

2 pages, 432 KB

Open AccessCorrection

Correction: Liu et al. A Semi-Analytical Loaded Contact Model and Load Tooth Contact Analysis Approach of Ease-Off Spiral Bevel Gears. Machines 2024, 12, 623

by Yuhui Liu, Liping Chen, Xian Mao and Duansen Shangguan

Machines 2026, 14(1), 18; https://doi.org/10.3390/machines14010018 - 22 Dec 2025

Abstract

There is an error in the original publication [...] Full article

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

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22 pages, 5185 KB

Open AccessArticle

AI-Based Predictive Maintenance for Rotor Crack Fault Diagnosis for Variable-Speed Machines Using Transfer Learning

by Sudhar Rajagopalan, Seemu Sharma and Ashish Purohit

Machines 2026, 14(1), 17; https://doi.org/10.3390/machines14010017 - 21 Dec 2025

Abstract

Fatigue-related ‘rotor crack’ can cause catastrophic failure if neglected. Thus, IoT-enabled AI-based predictive maintenance for fault detection and diagnosis is explored. Training and testing AI models under similar conditions improves their prediction performance. On variable speed machines, loss of performance occurs when the [...] Read more.

Fatigue-related ‘rotor crack’ can cause catastrophic failure if neglected. Thus, IoT-enabled AI-based predictive maintenance for fault detection and diagnosis is explored. Training and testing AI models under similar conditions improves their prediction performance. On variable speed machines, loss of performance occurs when the testing speed differs from the training speed. This research addresses significant performance loss issues using convolutional neural network (CNN)-based transfer learning models. The main causes of performance loss are domain shift, overfitting, data class imbalance, low fault data availability, and biassed prediction. All the above difficult issues make CNN-based fault prediction systems function badly under varying operating conditions. The proposed methodology addresses all domain adaptation challenges. The proposed methodology was tested by collecting vibration data from an experimental rotor system under varied operating conditions. The proposed methodology outperforms classical machine learning (ML) and deep learning (DL) models, overcoming the overfitting issue with optimised hyperparameters, achieving a prediction accuracy of 99.5%. Under varying operating conditions, it outperforms with a prediction accuracy of 93.2%, and in the ‘data class imbalanced’ scenario, the maximal transfer learning capability achieved was 84.4% with the highest F1-Score. Thus, CNN-based transfer learning enables industrial variable speed machines diagnose rotor crack flaws better than ML and DL models. Full article

(This article belongs to the Special Issue Intelligent Fault Diagnosis and Predictive Maintenance Systems: Advanced Methods for Industrial Equipment and Dynamic Operating Conditions)

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21 pages, 1718 KB

Open AccessArticle

Innovative Stability Design for a Specialized Handling Trolley for Sampling Devices

by Mária Vargovská, Roman Čierťažský and Elena Pivarčiová

Machines 2026, 14(1), 16; https://doi.org/10.3390/machines14010016 - 21 Dec 2025

Abstract

This article presents an analytical and simulation analysis of the stability of an innovative handling trolley. The analysis demonstrated that the loaded trolley (100 kg load) requires a critical tipping force F_crit of 502.24 N and a work W of 279.05 J. [...] Read more.

This article presents an analytical and simulation analysis of the stability of an innovative handling trolley. The analysis demonstrated that the loaded trolley (100 kg load) requires a critical tipping force F_crit of 502.24 N and a work W of 279.05 J. A comparative analysis confirmed a 128% higher force stability for the proposed solution compared to a standard model F_crit = 220 N. Following the structural design, a prototype was created and tested directly at the workplace for which it was designed; in addition to load tests, which it passed without issue, it was necessary to verify its stability. This step was approached from both a theoretical and practical standpoint. Given the need for special clamping of the transported material, a test was first performed on the empty handling trolley, and subsequently, the trolley was verified with the material clamped. This procedure was applied to the theoretical mathematical analytical solution, the simulation, and the practical test. This process required full consideration, given the manner of clamping, the robust and heavy nature of the transported material, and its operation by a single operator. In the practical test, pressure was applied to the trolley, both without load and with load, which verified and confirmed its stability in both longitudinal and transverse directions. The conclusions define that the trolley’s structure was even more stable after adding the load (handling material). A prototype was created and tested directly at the workplace. Practical stability tests were conducted by applying lateral pressure to both empty and loaded configurations, confirming stability in longitudinal and transverse directions. Formal tilt-table testing according to EN 1757 and ISO 22915 standards is planned for final certification. Full article

(This article belongs to the Special Issue Mechanics and Industrial Automation)

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46 pages, 7593 KB

Open AccessArticle

Optimization of End Mill Geometry for Machining 1.2379 Cold-Work Tool Steel Through Hybrid RSM-ANN-GA Coupled FEA Approach

by Tolga Berkay Şirin, Oguzhan Der, Hasan Kuş, Çağla Gökbulut Avdan, Semih Yüksel, Ayhan Etyemez and Mustafa Ay

Machines 2026, 14(1), 15; https://doi.org/10.3390/machines14010015 - 21 Dec 2025

Abstract

Optimizing end mill geometry is critical for improving performance and reducing costs in the high-volume manufacturing of tools, dies and molds. This study demonstrates a successful optimization framework for solid end mills machining 1.2379 cold-work tool steel, integrating Finite Element Analysis (FEA), Artificial [...] Read more.

Optimizing end mill geometry is critical for improving performance and reducing costs in the high-volume manufacturing of tools, dies and molds. This study demonstrates a successful optimization framework for solid end mills machining 1.2379 cold-work tool steel, integrating Finite Element Analysis (FEA), Artificial Neural Networks (ANN), and Genetic Algorithms (GA). The optimized tool geometry, derived from four key design parameters, delivered substantial performance gains over an industrial reference (parent) tool. Our ANN-GA model achieved a remarkable predictive accuracy (R = 0.75–0.98) over the RSM model (R = 0.17–0.63) and identified an optimal design that reduced the resultant cutting force by approximately 11% (to 142.8 N) and improved surface roughness by 21% (to 0.1637 µm) compared to experimental baselines. Crucially, the new geometry halved the tool breakage rate from 50% to ~25%. Parameter analysis revealed the width of the land as the most influential geometric factor. This work provides a validated, high-performance tool design and a powerful modeling framework for advancing machining efficiency in tool, mold and die manufacturing. Full article

(This article belongs to the Section Material Processing Technology)

21 pages, 897 KB

Open AccessArticle

Safety Assessment of Fuze Based on T-S Fuzzy Fault Tree and Interval Triangular Fuzzy Multi-State Bayesian Network

by Xue Wang, Ya Zhang, Shizhong Li and Bo Li

Machines 2026, 14(1), 14; https://doi.org/10.3390/machines14010014 - 21 Dec 2025

Abstract

In response to the relevant provisions of safety design criteria for fuze, and considering that Traditional Fault Tree Analysis (TFTA) struggles to describe system failure behavior, such as in its multi-state system faults and probabilistic logic linkages among components, this paper proposed a [...] Read more.

In response to the relevant provisions of safety design criteria for fuze, and considering that Traditional Fault Tree Analysis (TFTA) struggles to describe system failure behavior, such as in its multi-state system faults and probabilistic logic linkages among components, this paper proposed a method for analyzing fuze system failure based on the integration of T-S Fuzzy Fault Tree (T-SFFT) and Bayesian Network (BN), introducing an interval triangular fuzzy subset method for describing failure rates in the safety assessment of the fuze system. Taking the fault tree of the fuze function prior to the initiation of the ordained arming and safety-interruption sequence as an example, using this approach, the analysis and calculation results indicated that the fuzzy subsets of failure probability for the top event under the complete failure state of the fuze system were of the same order of magnitude as those obtained using the TFTA method. This therefore validated the feasibility and effectiveness of this method in fuze system safety assessment. Furthermore, using BN to obtain the posterior probabilities of nodes, this approach provided a data foundation for fuze system fault diagnosis, holding significant engineering significance for fuze system safety assessment. Full article

(This article belongs to the Special Issue Reliability in Mechanical Systems: Innovations and Applications)

17 pages, 762 KB

Open AccessArticle

Robust Control of Offshore Container Cranes: 3D Trajectory Tracking Under Marine Disturbances

by Ao Li, Shuzhen Li, Phuong-Tung Pham and Keum-Shik Hong

Machines 2026, 14(1), 13; https://doi.org/10.3390/machines14010013 - 20 Dec 2025

Abstract

This paper develops accurate three-dimensional trajectory tracking and anti-sway control strategies for offshore container cranes operating in an open-sea environment. A 5-DOF nonlinear dynamic model is developed that simultaneously accounts for the crane’s structural motion, trolley movement, spreader hoisting with variable rope length, [...] Read more.

This paper develops accurate three-dimensional trajectory tracking and anti-sway control strategies for offshore container cranes operating in an open-sea environment. A 5-DOF nonlinear dynamic model is developed that simultaneously accounts for the crane’s structural motion, trolley movement, spreader hoisting with variable rope length, and both lateral and longitudinal payload sway. The model further incorporates external disturbances induced by wave-excited ship motions. To ensure smooth, efficient, and accurate load transportation from the initial to the target position, an effective trajectory-planning scheme is proposed using a quintic polynomial trajectory refined by a ZVD shaper to suppress residual oscillations. A sliding mode control method is then designed to achieve accurate trajectory tracking and load-sway suppression under external disturbances. Numerical simulations demonstrate that the proposed trajectory planning method effectively reduces the residual oscillations and verifies the effectiveness and robustness of the proposed sliding mode control strategy. Full article

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

19 pages, 8369 KB

Open AccessArticle

An Ensemble-LSTM-Based Framework for Improved Prognostics and Health Management of Milling Machine Cutting Tools

by Sahbi Wannes, Lotfi Chaouech, Jaouher Ben Ali, Eric Bechhoefer and Mohamed Benbouzid

Machines 2026, 14(1), 12; https://doi.org/10.3390/machines14010012 - 20 Dec 2025

Abstract

Accurate Prognostics and Health Management (PHM) of cutting tools in Computer Numerical Control (CNC) milling machines is essential for minimizing downtime, improving product quality, and reducing maintenance costs. Previous studies have frequently applied deep learning, particularly Long Short-Term Memory (LSTM) neural networks, for [...] Read more.

Accurate Prognostics and Health Management (PHM) of cutting tools in Computer Numerical Control (CNC) milling machines is essential for minimizing downtime, improving product quality, and reducing maintenance costs. Previous studies have frequently applied deep learning, particularly Long Short-Term Memory (LSTM) neural networks, for tool wear prediction and Remaining Useful Life (RUL) prediction. However, they often rely on simplified datasets or single architectures limiting industrial relevance. This study proposes a novel ensemble-LSTM framework that combines LSTM, BiLSTM, Stacked LSTM, and Stacked BiLSTM architectures using a GRU-based meta-learner to exploit their complementary strengths. The framework is evaluated using the publicly available PHM’2010 milling dataset, a well-established industrial benchmark comprising comprehensive time-series sensor measurements collected under variable loads and realistic machining conditions. Experimental results show that the ensemble-LSTM outperforms individual LSTM models, achieving an RMSE of 2.4018 and an MAE of 1.9969, accurately capturing progressive tool wear trends and adapting to unseen operating conditions. The approach provides a robust, reliable solution for real-time predictive maintenance and demonstrates strong potential for industrial tool condition monitoring. Full article

(This article belongs to the Special Issue Digital Twins and Advanced Fault Modeling in the Condition Monitoring of Electric Machines)

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19 pages, 3914 KB

Open AccessArticle

Analysis and Experiment of Damping Characteristics of Multi-Hole Pressure Pulsation Attenuator

by Shenghao Zhou, Na Zhou, Yukang Zhang, Guoshuai Wang, Xinyu Li, Hui Ma and Junzhe Lin

Machines 2026, 14(1), 11; https://doi.org/10.3390/machines14010011 - 19 Dec 2025

Abstract

Aviation hydraulic systems operate under high pressure and large flow rates, which induce significant fluid pressure pulsations and hydraulic shocks in pipelines. These pulsations, exacerbated by complex external loads, can lead to excessive vibration stress, component damage, oil leakage, and compromised system safety. [...] Read more.

Aviation hydraulic systems operate under high pressure and large flow rates, which induce significant fluid pressure pulsations and hydraulic shocks in pipelines. These pulsations, exacerbated by complex external loads, can lead to excessive vibration stress, component damage, oil leakage, and compromised system safety. While existing methods—such as pump structure optimization, pipeline layout adjustment, and active control—can reduce pulsations to some extent, they are limited by cost, reliability, and adaptability, particularly under high-pressure and multi-excitation conditions. Passive control, using pressure pulsation damping devices, has proven to be more practical; however, conventional designs typically focus on low-load systems and have limited frequency adaptability. This paper proposes a multi-hole parallel pressure pulsation damping device that offers high vibration attenuation, broad adaptability, and easy installation. A combined simulation–experiment approach is employed to investigate its damping mechanism and performance. The results indicate that the damping device effectively reduces vibrations in the 200–500 Hz range, with minimal impact from changes in load pressure and rotational speed. Under a high pressure of 21 MPa and a speed of 1500 rpm, the maximum insertion loss can reach 15.82 dB, significantly reducing the pressure pulsation in the hydraulic pipeline. Full article

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

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29 pages, 28063 KB

Open AccessArticle

Braking Energy Recovery Control Strategy Based on Instantaneous Response and Dynamic Weight Optimization

by Lulu Cai, Pengxiang Yan, Xiaopeng Yang, Liyu Yang, Yi Liu, Guanfu Huang, Shida Liu and Jingjing Fan

Machines 2026, 14(1), 10; https://doi.org/10.3390/machines14010010 - 19 Dec 2025

Abstract

Multi-axle electric heavy-duty trucks face significant challenges in maintaining braking stability and achieving real-time control during regenerative braking due to their large mass and complex inter-axle coupling dynamics. To address these issues, this paper proposes an improved model predictive control (IMPC) strategy that [...] Read more.

Multi-axle electric heavy-duty trucks face significant challenges in maintaining braking stability and achieving real-time control during regenerative braking due to their large mass and complex inter-axle coupling dynamics. To address these issues, this paper proposes an improved model predictive control (IMPC) strategy that enhances computational efficiency and control responsiveness through an instantaneous response mechanism. The approach integrates a first-order error attenuation term within the MPC framework and employs an extended Kalman filter to estimate tire–road friction in real time, enabling adaptive adjustment between energy recovery and stability objectives under varying road conditions. A control barrier function constraint is further introduced to ensure smooth and safe regenerative braking. Simulation results demonstrate improved energy recovery efficiency and faster convergence, while real-vehicle tests confirm that the IMPC maintains superior real-time performance and adaptability under complex operating conditions, reducing average computation time by approximately 14% compared with conventional MPC and showing strong potential for practical deployment. Full article

(This article belongs to the Special Issue Active and Passive Safety and Noise, Vibration, and Harshness (NVH) of Intelligent Vehicles)

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29 pages, 26080 KB

Open AccessArticle

A Machine Learning Vibration-Based Methodology for Robust Detection and Severity Characterization of Gear Incipient Faults Under Variable Working Speed and Load

by Dimitrios M. Bourdalos and John S. Sakellariou

Machines 2026, 14(1), 9; https://doi.org/10.3390/machines14010009 - 19 Dec 2025

Abstract

A machine learning (ML) methodology for the robust detection and severity characterization of incipient gear faults under variable speed and load is postulated. The methodology is trained using vibration signals from a single accelerometer mounted on the gearbox, simultaneously acquired with tachometer signals [...] Read more.

A machine learning (ML) methodology for the robust detection and severity characterization of incipient gear faults under variable speed and load is postulated. The methodology is trained using vibration signals from a single accelerometer mounted on the gearbox, simultaneously acquired with tachometer signals at a sample of working conditions (WCs) from the range of interest. A special parametric identification procedure of gearbox dynamics that may account for the continuous range of WCs is introduced through `clouds’ of advanced stochastic data-driven Functionally Pooled models, estimated from angularly resampled vibration signals. Each cloud represents the gearbox dynamics at a specific fault severity level, while the pseudo-static effects of the WCs on the dynamics are accounted for through data pooling. Fault detection and severity characterization are achieved by testing the consistency of a vibration signal with each model cloud within a hypothesis testing framework in which the unknown load is also estimated. The methodology is assessed through 18,300 experiments on a single-stage spur gearbox including four incipient single-tooth pinion faults, 61 speeds, and four load levels. The faults produce no significant changes in the time-domain signals, while their frequency-domain effects overlap with the variations caused by the WCs, rendering the diagnosis problem highly challenging. The comparison with a state-of-the-art deep Stacked Autoencoder (SAE) demonstrates the ML method’s superior performance, achieving 95.4% and 91.6% accuracy in fault detection and characterization, respectively. Full article

(This article belongs to the Special Issue Intelligent Vibration Control and Condition Monitoring in Smart Structures and Electromechanical Systems)

25 pages, 5866 KB

Open AccessArticle

Quantitative Evaluation of an Industrial Robot Tool Trajectory Deviation Using a High-Speed Camera

by Mantas Makulavičius, Sigitas Petkevičius, Vytautas Bučinskas and Andrius Dzedzickis

Machines 2026, 14(1), 8; https://doi.org/10.3390/machines14010008 - 19 Dec 2025

Abstract

One of the primary applications of industrial robots is in various manufacturing processes, such as milling, grinding, and additive manufacturing. To achieve the desired precision in tool trajectory performance when machining specific parts, it is necessary to calibrate the tool centre point (TCP) [...] Read more.

One of the primary applications of industrial robots is in various manufacturing processes, such as milling, grinding, and additive manufacturing. To achieve the desired precision in tool trajectory performance when machining specific parts, it is necessary to calibrate the tool centre point (TCP) of the robot for each manufacturing process. The development of industrial robot tool trajectories is a multipurpose task. It encompasses issues related to robot geometry, path interpolation type, and trajectory waypoints approximation. The primary objective of this study is to establish a camera-based methodology for evaluating trajectory-following accuracy in industrial robots. The present paper proposes the use of a high-speed motion camera system for non-contact tracking of TCP trajectories. By capturing the robot’s end-effector motion in real-time and under actual trajectory tracking conditions, this technique enables a clearer understanding of how trajectory execution accuracy varies with velocity, trajectory geometry, trajectory interpolation, and robot kinematics. Provided analysis of two industrial robot types opened interesting findings related to the dependencies between the implementation of first- and second-degree interpolations. To illustrate this point, the implementation of second-degree interpolation ensures a more consistent velocity in the trajectory. This contrasts with first-degree interpolation, which is more challenging to achieve and is susceptible to variations in curvature. Conversely, the utilization of first-degree interpolation facilitates enhanced performance accuracy for smaller curvatures. The results of the experimental research confirm the initial hypothesis regarding the influence of interpolation mode and pave the way for future uses of this information for machine learning algorithms. Full article

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

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30 pages, 4538 KB

Open AccessArticle

Operator-Based Direct Nonlinear Control Using Self-Powered TENGs for Rectifier Bridge Energy Harvesting

by Chengyao Liu and Mingcong Deng

Machines 2026, 14(1), 7; https://doi.org/10.3390/machines14010007 - 19 Dec 2025

Abstract

Triboelectric nanogenerators (TENGs) offer intrinsically high open-circuit voltages in the kilovolt range; however, conventional diode rectifier interfaces clamp the voltage prematurely, restricting access to the high-energy portion of the mechanical cycle and preventing delivery-centric control. This work develops a unified physical basis for [...] Read more.

Triboelectric nanogenerators (TENGs) offer intrinsically high open-circuit voltages in the kilovolt range; however, conventional diode rectifier interfaces clamp the voltage prematurely, restricting access to the high-energy portion of the mechanical cycle and preventing delivery-centric control. This work develops a unified physical basis for contact–separation (CS) TENGs by confirming the consistency of the canonical

V_{o c}

–

C_{s}

relation with a dual-capacitor energy model and analytically establishing that both terminal voltage and storable electrostatic energy peak near maximum plate separation. Leveraging this insight, a self-powered gas-discharge-tube (GDT) rectifier bridge is devised to replace two diodes and autonomously trigger conduction exclusively in the high-voltage window without auxiliary bias. An inductive buffer regulates the current slew rate and reduces

I^{2} R

loss, while the proposed topology realizes two decoupled power rails from a single CS-TENG, enabling simultaneous sensing/processing and actuation. A low-power microcontroller is powered from one rail through an energy-harvesting module and executes an operator-based nonlinear controller to regulate the actuator-side rail via a MOSFET–resistor path. Experimental results demonstrate earlier and higher-efficiency energy transfer compared with a diode-bridge baseline, robust dual-rail decoupling under dynamic loading, and accurate closed-loop voltage tracking with negligible computational and energy overhead. These findings confirm the practicality of the proposed self-powered architecture and highlight the feasibility of integrating operator-theoretic control into TENG-driven rectifier interfaces, advancing delivery-oriented power extraction from high-voltage TENG sources. Full article

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

16 pages, 1259 KB

Open AccessArticle

Impact and Detection of Coil Asymmetries in a Permanent Magnet Synchronous Generator with Parallel Connected Stator Coils

by Nikolaos Gkiolekas, Alexandros Sergakis, Marios Salinas, Markus Mueller and Konstantinos N. Gyftakis

Machines 2026, 14(1), 6; https://doi.org/10.3390/machines14010006 - 19 Dec 2025

Abstract

Permanent magnet synchronous generators (PMSGs) are suitable for offshore applications due to their high efficiency and power density. Inter-turn short circuits (ITSCs) stand as one of the most critical faults in these machines due to their rapid evolution in phase or ground short [...] Read more.

Permanent magnet synchronous generators (PMSGs) are suitable for offshore applications due to their high efficiency and power density. Inter-turn short circuits (ITSCs) stand as one of the most critical faults in these machines due to their rapid evolution in phase or ground short circuits. It is therefore necessary to detect ITSCs at an early stage. In the literature, ITSC detection is often based on current signal processing methods. One of the challenges that these methods face is the presence of imperfections in the stator coils, which also affects the three-phase symmetry. Moreover, when the stator coils are connected in parallel, this type of fault becomes important, as circulating currents will flow between the parallel windings. This, in turn, increases the thermal stress on the insulation and the permanent magnets, while also exacerbating the vibrations of the generator. In this study, a finite-element analysis (FEA) model has been developed to simulate a dual-rotor PMSG under conditions of coil asymmetry. To further investigate the impact of this asymmetry, mathematical modeling has been conducted. For fault detection, negative-sequence current (NSC) analysis and torque monitoring have been used to distinguish coil asymmetry from ITSCs. While both methods demonstrate potential for fault identification, NSC induced small amplitudes and the torque analysis was unable to detect ITSCs under low-severity conditions, thereby underscoring the importance of developing advanced strategies for early-stage ITSC detection. The innovative aspect of this work is that, despite these limitations, the combined use of NSC phase-angle tracking and torque harmonic analysis provides, for the first time in a core-less PMSG with parallel-connected coils, a practical way to distinguish ITSC from coil asymmetry, even though both faults produce almost identical signatures in conventional current-based indices. Full article

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

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19 pages, 4518 KB

Open AccessArticle

Dynamic Damage Behavior Analysis of Hail Impact on Composite Radome Structure Using Peridynamic Bond-Based Theory

by Feng Zhang, Yuxiao Xu, Xiayu Xu, Lingwei Bai, Xiaoxiao Liu and Yazhou Guo

Machines 2026, 14(1), 5; https://doi.org/10.3390/machines14010005 - 19 Dec 2025

Abstract

This paper studies the progressive damage process and final damage form of composite laminate aircraft radome under high-speed hail impact A simulation method based on Peridynamic bond-based theory is proposed to study the progressive damage process and final damage form of composite laminate [...] Read more.

This paper studies the progressive damage process and final damage form of composite laminate aircraft radome under high-speed hail impact A simulation method based on Peridynamic bond-based theory is proposed to study the progressive damage process and final damage form of composite laminate aircraft radome under high-speed hail impact. Using the Peridynamic theory, the dynamic damage behavior of hailstone impact on a composite laminate plate is analyzed, and an impact model of hailstone impact is established to study the damage initiation, expansion, and failure behavior of the composite laminate. The dynamic mechanical constitutive and failure criteria that characterize the macromechanical behavior of both hailstone and composite laminate during impact are established. Additionally, equations describing the interaction forces between these two materials are proposed to develop a numerical simulation method for the laminate failure process. The dynamic damage evolution and failure mechanisms are subsequently investigated to provide a theoretical foundation for the optimum design of composite structures, such as aircraft radomes, subjected to hail impact. To describe the interaction force equations between two materials, a new method based on Peridynamics (PD) is proposed to establish a numerical simulation method for the damage process of laminated plates. This method provides a theoretical basis for optimizing the design of composite structures (such as aircraft radome) after being impacted by hail. Full article

(This article belongs to the Special Issue Advanced Aircraft Aerodynamics, Flight Stability, Stabilization and Control of Flying Vehicles)

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13 pages, 2449 KB

Open AccessArticle

Dynamic System Analysis of Vent and Recycle Configurations in Centrifugal Compressors

by Andrea Betti, Leonardo Cappelli, Andrea Fusi, Fulvio Palmieri and Luigi Tundo

Machines 2026, 14(1), 4; https://doi.org/10.3390/machines14010004 - 19 Dec 2025

Abstract

Centrifugal compressors are vital components in industrial applications, but they are prone to a disruptive phenomenon known as surge, which can lead to mechanical stress and temperature increase. Surge occurrence is influenced by machine design, plant layout, and geometry. Engineers often deploy long [...] Read more.

Centrifugal compressors are vital components in industrial applications, but they are prone to a disruptive phenomenon known as surge, which can lead to mechanical stress and temperature increase. Surge occurrence is influenced by machine design, plant layout, and geometry. Engineers often deploy long (cold) and short (hot) recycle valves to address this issue. To ensure surge prevention, a fluid dynamic model is indispensable. In this study, a 1D Computational Fluid Dynamics (1D-CFD) model was developed using Amesim for a two-section centrifugal compressor. The main objective was to investigate the impact of various parameters on surge occurrence and compare different plant layouts to determine the most suitable solution for the specific study case. Here, the focus is on the influence of vent valves over the plant performance. To achieve this comparison, transient simulations of emergency shutdown (ESD) operations were performed. This study contributes to a better understanding of how machine design and operational factors affect surge behavior. By systematically evaluating different plant layouts, we identified the most effective strategies for preventing surge and enhancing compressor performance. This research provides valuable insights for engineers and operators striving to optimize industrial processes and improve the reliability and efficiency of centrifugal compressor systems. Full article

(This article belongs to the Section Turbomachinery)

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