Vibration Damping

A special issue of Vibration (ISSN 2571-631X).

Deadline for manuscript submissions: 15 December 2025 | Viewed by 1056

Special Issue Editors


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Guest Editor
CNRS, Arts et Métiers ParisTech, LEM3, Université de Lorraine, 57000 Metz, France
Interests: vibration control; energy harvesting; active vibration control; viscoelastic sandwich; design optimisation uncertainty propagation; kriging surrogates; proper orthogonal decomposition

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Guest Editor
Luxembourg Institute of Science and Technology, 5 Av. des Hauts-Fourneaux, Esch-Belval Esch-sur-Alzette, 4362 Luxembourg, Luxembourg
Interests: multidisciplinary design optimization; FGM; active vibration control; finite element method; smart material; applied mechanics

Special Issue Information

Dear Colleagues,

Vibration control consists of attenuating excessive amplitudes of oscillations and suppressing undesirable resonances to avoid premature fatigue failure of structural components. The use of one form of vibration control or another in most newly designed structures is becoming commonplace to meet the pressing needs for large and lightweight structures. Various passive, active and hybrid vibration control approaches have been considered over the years, employing a variety of structural designs, damping materials, active control laws, actuators and sensors. While most approaches appearing in the literature rely on dissipating mechanical energy for vibration control purposes, vibration energy harvesting that aims at providing energy for low-power wireless sensor networks and microelectronic systems offers an alternative way to damp unwanted vibrations, employing various conversion techniques and using specialized electronic interfaces that perform a nonlinear active treatment of the voltage generated by the harvester, inspired by the synchronized switch damping method. This Special Issue is dedicated to the topic of vibration damping and seeks the most recent advances recorded therein. It particularly focuses on passive damping systems such as constrained layer damping, shunted piezoelectric treatments, damping layers with shunted piezoelectric treatments, magnetic constrained layer damping, shape memory alloy damping, active vibration control systems with piezoelectric layers such as active constrained layer damping, active piezoelectric damping composites, electromagnetic damping composites, active shunted piezoelectric networks and finally on vibration energy harvesting devices using piezoelectric, electromagnetic, electrostatic or hybrid conversion mechanisms. It emphasizes approaches based on mathematical modeling, nonlinear dynamical system analysis, finite element modeling and simulation, optimal design, uncertainty quantification, nonlinear recovery circuits and experimental proof of concepts for vibration damping purposes. The main objective is to provide a broad overview of recent developments and results in this field, as well as an idea of the potential for their extension and generalization to current and future industry applications.

Dr. Mohamed Hamdaoui
Dr. Kouider Bendine
Guest Editors

Manuscript Submission Information

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Keywords

  • viscoelastic damping
  • vibration energy harvesting
  • active vibration control
  • hybrid vibration control
  • mathematical modeling
  • finite Elements modeling
  • nonlinear dynamical system analysis
  • optimal design
  • uncertainty quantification
  • experimental proof of concepts
  • nonlinear recovery circuits

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Published Papers (1 paper)

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Research

31 pages, 25255 KiB  
Article
Fault Classification in Diesel Engines Based on Time-Domain Responses through Signal Processing and Convolutional Neural Network
by Gabriel Hasmann Freire Moraes, Ronny Francis Ribeiro Junior and Guilherme Ferreira Gomes
Vibration 2024, 7(4), 863-893; https://doi.org/10.3390/vibration7040046 - 29 Sep 2024
Viewed by 644
Abstract
In today’s interconnected industrial landscape, the ability to predict and monitor the operational status of equipment is crucial for maintaining efficiency and safety. Diesel engines, which are integral to numerous industrial applications, require reliable fault detection mechanisms to reduce operational costs, prevent unplanned [...] Read more.
In today’s interconnected industrial landscape, the ability to predict and monitor the operational status of equipment is crucial for maintaining efficiency and safety. Diesel engines, which are integral to numerous industrial applications, require reliable fault detection mechanisms to reduce operational costs, prevent unplanned downtime, and extend equipment lifespan. Traditional anomaly detection methods, such as thermometry, wear indicators, and radiography, often necessitate significant expertise, involve costly equipment shutdowns, and are limited by high usage costs and accessibility. Addressing these challenges, this study introduces a novel approach for fault detection in diesel engines by analyzing torsional vibration data in the time domain. The proposed method leverages short-term Fourier transform (STFT) and continuous wavelet transform (CWT) techniques, integrated with a convolutional neural network (CNN) to identify hidden patterns and diagnose engine conditions accurately. The method achieved a detection accuracy of 96.5% with STFT and 92.2% with CWT. To ensure robustness, the model was tested under various noise conditions, maintaining accuracies above 70% for noise levels up to 40%. This research provides a practical and efficient solution for real-time fault detection in diesel engines, offering a significant improvement over traditional methods in terms of cost, accessibility, and ease of implementation. Full article
(This article belongs to the Special Issue Vibration Damping)
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