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Machines MDPI

Machines (ISSN 2075-1702, IF: 3.0, CiteScore: 6.1) - Open Access Journal on machinery and engineering, published monthly online by MDPI.

28/08/2026

: "VR Co‑Lab: A Virtual Reality Platform for Human–Robot Disassembly Training and Synthetic Data Generation"
👨‍🏫 Author: Yashwanth Maddipatla, Sibo Tian, Xiao Liang, Minghui Zheng, Beiwen Li
👉 More information: https://www.mdpi.com/2075-1702/13/3/239
✨ Citations: 9

📖 This work introduces VR Co‑Lab, a VR‑based immersive training platform targeting human‑robot collaborative disassembly, especially for e‑waste recycling. Built on Unity‑ROS bridge and Meta Quest Pro full body tracking, it supports multi‑robot simulation via URDF files and generates synthetic interaction datasets. An LSTM model combined with Monte Carlo dropout achieves uncertainty‑aware real‑time prediction of human‑robot motion, deployed locally with Unity Barracuda engine to cut inference latency. Taking hard disk disassembly as the test scenario, the platform delivers real‑time visual auditory feedback and metrics dashboard for task completion time, error rate and user engagement. Preliminary tests show improved task efficiency and human‑robot motion alignment. The study points out current limitations including lack of multi‑user mode, tracking noise and insufficient real world industrial validation. It offers a sandbox solution for safe, repeatable HRC training and data collection, and outlines future directions: multi‑user scenarios, eye‑tracking integration, alternative prediction architectures and real‑site skill transfer validation.

Iowa State University
Texas A&M University
University of Georgia
MDPI

28/08/2026

📣 The first paper "A Gated Multi-Source Signal Fusion Method for Fault with a Fusion Negative-Transfer Suppression Mechanism" has been published online in the "Advanced , and Intelligent of Rolling " edited by Dr. Mohamed Nassef and Dr. Florian Pape, which is open for submission now.

👉 Details: https://www.mdpi.com/journal/machines/special_issues/D9907D88XX
🎰 Submission deadline: 31 December 2026

Egypt Japan University of Science and Technology - EJUST
Leibniz Universität Hannover

MDPI

28/08/2026

🔓 Special Issue "Intelligent Robotics and Autonomous Systems for Complex Environments" edited by Dr. Zhijie Li, Dr. Qin Zhou, Prof. Dr. Hua Zhang, and Prof. Dr. En Li

👉 Welcome your submission:
https://www.mdpi.com/journal/machines/special_issues/7MFLFA55OB
📅 Submission date: 30 April 2027

27/08/2026

🔓The 8th issue in 2026 of Machines MDPI has been released, in which 121 manuscripts were published👏.

📰Cover Story: "Explainable Thermographic Fault Diagnosis of Three‑Phase Induction Motors Using Transient Thermal Signatures: A Case Study" by Miguel Enrique Iglesias Martínez, JOSE ANTONINO-DAVIU, Larisa Dunai Dunai, María J. Picazo-Ródenas, J. Alberto Conejero Casares, Humberto Michinel, and Pedro Fernández de Córdoba Castellá

📖This paper proposes an explainable thermography based diagnostic framework for three‑phase induction motors. Two physically derived indices are developed to discriminate cooling failure and phase unbalance faults. This non‑contact monitoring approach avoids black‑box machine learning models and offers physical interpretability for real‑world motor condition‑monitoring scenarios.

👉Read more about Issue at: https://www.mdpi.com/2075-1702/14/8
🔗Read the Cover Article: https://www.mdpi.com/2075-1702/14/8/843

27/08/2026

🔓 Special Issue "Artificial Intelligence in Wind Energy Optimization Design" edited by Prof. Dr. Andy Chit Tan from Universiti Tunku Abdul Rahman (UTAR) and Prof. Dr. Longyan Wang from Jiangsu University

👉 Welcome your submission:
https://www.mdpi.com/journal/machines/special_issues/W7G7WEBGEN

📅 Submission date: 31 January 2027

26/08/2026

: "Current Trends in Monitoring and Analysis of Tool Wear and Delamination in Wood‑Based Panels Drilling"
👨‍🏫 Author: Tomasz Trzepieciński, Krzysztof Szwajka, Joanna Zielińska‑Szwajka, Marek Szewczyk
👉 More information: https://www.mdpi.com/2075-1702/13/3/249
✨ Citations: 10

MDPI

26/08/2026

: "Analysis of Electromagnetic Vibration in Permanent Magnet Motors Based on Random PWM Technology"
👨‍🏫 Author: Chi Ma, Yongxiang Wang, Huang Chen, Jianfeng Hong, Yi Wang
👉 More information: https://www.mdpi.com/2075-1702/13/4/259

📖 This paper investigates high‑frequency electromagnetic vibration of inverter‑fed permanent magnet motors, comparing periodic PWM (PPWM) and random switching frequency PWM (RPWM). It first analyses high‑order stator current harmonics and the corresponding electromagnetic force excitation mechanism. Both simulation and prototype experiments show that periodic PWM and random switching frequency PWM can greatly attenuate narrow‑band harmonic amplitudes around carrier frequency and its multiples, effectively suppressing sharp audible high‑frequency noise. Nevertheless, spectral spreading disperses harmonic energy across wider bands; therefore the overall total vibration level cannot be reduced. The study also notes that increasing random frequency bandwidth suppresses harmonic peaks yet raises current total harmonic distortion (THD) and torque ripple. This work provides practical reference for understanding the real‑world noise‑reduction limits of random‑PWM schemes for traction permanent‑magnet motors.

Beijing Jiaotong University
MDPI

26/08/2026

🔓 Special Issue "Advanced Vibration and Noise Control Technologies for Mechanical Systems" edited by Dr. Abdallah Abbas Galal

👉 Welcome your submission: https://www.mdpi.com/journal/machines/special_issues/EN5UDS6D40

📅 Submission date: 30 April 2027

25/08/2026

: "Streamlined Bearing Fault Detection Using Artificial Intelligence in Permanent Magnet Synchronous Motors"
👨‍🏫Author: Javier de las Morenas, Lidia M. Belmonte, Rafael Morales
👉More information: https://www.mdpi.com/2075-1702/13/5/357
✨Citations: 10

📖 This work proposes an edge‑fog‑cloud hierarchical architecture for bearing fault diagnosis of permanent magnet synchronous motors (PMSMs). The non‑intrusive scheme only uses single‑phase stator current signals, avoiding extra vibration sensors. Fast Fourier transform (FFT) and Hilbert‑transform‑based envelope analysis are adopted for signal preprocessing to extract fault‑related harmonics masked by fundamental frequency. This solution offers a cost‑effective route for industrial predictive maintenance of PMSM drives.

Universidad de Castilla-La Mancha
MDPI

25/08/2026

🏆Editor's Choice Article
: "Numerical Simulation and Experimental Study of Piston Rebound Energy Storage Characteristics for Nitrogen‑Hydraulic Combined Impact Hammer"
👨‍🏫 Author: Hu Chen, Boqiang Shi, Hui Guo
👉 More information: https://www.mdpi.com/2075-1702/13/2/97

📖 This work investigates piston rebound energy storage performance of nitrogen‑hydraulic combined impact hammers widely used in mining and demolition. The authors built system dynamic equations and a complete AMEsim numerical model covering piston, reversing valve, accumulator and drill rod. The research reveals that the opening percentage of the reversing‑valve high‑pressure port at rebound onset dominates rebound energy‑recovery. Key structural parameters including piston middle‑section length and number of high‑pressure grooves in signal chamber were studied. Optimized structural parameters effectively recover piston rebound kinetic energy, reduce back‑chamber peak pressure, improve system stability, and boost impact frequency, impact power and overall energy utilization. This study supplies practical reference for performance analysis and structural optimization of hydropneumatic impact hammers.

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