Machines | Highly Cited Papers Published in 2025

In order to highlight impactful research from 2025, we invite you to read the highly cited papers from 2025 published in our journal Machines (ISSN 2075-1702). We hope they will offer you cutting-edge perspectives in this field and assist with your research.

1. “Resistance Spot Welding Defect Detection Based on Visual Inspection: Improved Faster R-CNN Model”
by Weijie Liu, Jie Hu and Jin Qi
Machines 2025, 13(1), 33; https://doi.org/10.3390/machines13010033
Available online: https://www.mdpi.com/2075-1702/13/1/33

2. “An Optimized Few-Shot Learning Framework for Fault Diagnosis in Milling Machines”
by Faisal Saleem, Muhammad Umar and Jong-Myon Kim
Machines 2025, 13(11), 1010; https://doi.org/10.3390/machines13111010
Available online: https://www.mdpi.com/2075-1702/13/11/1010

3. “A Novel Bearing Fault Diagnosis Method Based on Improved Convolutional Neural Network and Multi-Sensor Fusion”
by Zhongyao Wang, Xiao Xu, Dongli Song, Zejun Zheng and Weidong Li
Machines 2025, 13(3), 216; https://doi.org/10.3390/machines13030216
Available online: https://www.mdpi.com/2075-1702/13/3/216

4. “Condition Monitoring and Fault Prediction in PMSM Drives Using Machine Learning for Elevator Applications”
by Vasileios I. Vlachou, Theoklitos S. Karakatsanis, Dimitrios E. Efstathiou, Eftychios I. Vlachou, Stavros D. Vologiannidis, Vasiliki E. Balaska and Antonios C. Gasteratos
Machines 2025, 13(7), 549; https://doi.org/10.3390/machines13070549
Available online: https://www.mdpi.com/2075-1702/13/7/549

5. “A Hierarchical and Self-Evolving Digital Twin (HSE-DT) Method for Multi-Faceted Battery Situation Awareness Realisation”
by Kai Zhao, Ying Liu, Yue Zhou, Wenlong Ming and Jianzhong Wu
Machines 2025, 13(3), 175; https://doi.org/10.3390/machines13030175
Available online: https://www.mdpi.com/2075-1702/13/3/175

6. “Experimental Validation and Dynamic Analysis of Additive Manufacturing Burner for Gas Turbine Applications”
By Alessio Cascino, Enrico Meli, Andrea Rindi, Egidio Pucci and Emanuele Matoni
Machines 2025, 13(12), 1111; https://doi.org/10.3390/machines13121111
Available online: https://www.mdpi.com/2075-1702/13/12/1111

7. “Experimental Identification of Milling Process Damping and Its Application in Stability Lobe Diagrams”
by Cvijetin Mladjenovic, Katarina Monkova, Aleksandar Zivkovic, Milos Knezev, Dejan Marinkovic and Vojin Ilic
Machines 2025, 13(2), 96; https://doi.org/10.3390/machines13020096
Available online: https://www.mdpi.com/2075-1702/13/2/96

8. “VR Co-Lab: A Virtual Reality Platform for Human–Robot Disassembly Training and Synthetic Data Generation”
by Yashwanth Maddipatla, Sibo Tian, Xiao Liang, Minghui Zheng and Beiwen Li
Machines 2025, 13(3), 239; https://doi.org/10.3390/machines13030239
Available online: https://www.mdpi.com/2075-1702/13/3/239

9. “Real-Time Modeling of Static, Dynamic and Mixed Eccentricity in Permanent Magnet Synchronous Machines”
by Ramón Pérez, Jérôme Cros and Mathieu Picard
Machines 2025, 13(2), 120; https://doi.org/10.3390/machines13020120
Available online: https://www.mdpi.com/2075-1702/13/2/120

10. “Development of a Fault-Tolerant Permanent Magnet Synchronous Motor Using a Machine-Learning Algorithm for a Predictive Maintenance Elevator”
by Vasileios I. Vlachou and Theoklitos S. Karakatsanis
Machines 2025, 13(5), 427; https://doi.org/10.3390/machines13050427
Available online: https://www.mdpi.com/2075-1702/13/5/427