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Sensing Technologies and Measurement Techniques in Mechanical Vibrations and Structural Dynamics

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 1704

Special Issue Editors


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Guest Editor
Department of Mechanical and Construction Engineering, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
Interests: theoretical and experimental structural dynamics; vibration analysis; FE model updating
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK
Interests: aero-structures; loads and aeroelasticity; morphing technology; dynamics and vibration; aircraft design; mechanics and composite materials characterization

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Guest Editor
Department of Mechanical Engineering, Arak University of Technology, Arak 38181-41167, Iran
Interests: experimental vibration analysis; chatter vibrations in machining processes; vibration of robotic processes; machining dynamics; rotor dynamics of turbomachinery; modal testing; robotics

Special Issue Information

Dear Colleagues,

The main scope of this special issue is to gather state-of-the-art research adding the latest scientific advancements in the field of mechanical vibrations and structural dynamics. It will combine fundamental research on sensing technology, measurement, modeling and identification techniques used in mechanical structures and other relevant engineering applications. The presented papers are expected to make demonstrable original contributions to the scientific world.

Structural vibration has a significant impact on the integrity/performance of the structures. For instance, structural vibration plays a key role in the design stage of many Mechanical Engineering applications in aerospace, automotive and energy (i.e., rotating machinery) industries. The scope covered in this special issue includes, but is not limited to, topics such as Structural dynamics, Inverse problems in vibration, Improvement of finite element models using experimental data, Modelling and identification of nonlinear mechanical joints, Frictional contact interface modelling, Uncertainty quantification in structural dynamics, Dynamics of rotating machinery and Machining vibrations.

Dr. Hassan Jalali
Dr. Mohammadreza Amoozgar
Dr. Farzad Rafieian
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • structural dynamics
  • dynamics of rotating machinery
  • machining vibrations
  • experimental and analytical vibration analysis

Published Papers (1 paper)

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Research

19 pages, 6273 KiB  
Article
Identification of Time-Varying External Force Using Group Sparse Regularization and Redundant Dictionary
by Huanlin Liu and Hongwei Ma
Sensors 2023, 23(1), 151; https://doi.org/10.3390/s23010151 - 23 Dec 2022
Cited by 1 | Viewed by 1364
Abstract
How to accurately identify unknown time-varying external force from measured structural responses is an important engineering problem, which is critical for assessing the safety condition of the structure. In the context of a few available accelerometers, this paper proposes a novel time-varying external [...] Read more.
How to accurately identify unknown time-varying external force from measured structural responses is an important engineering problem, which is critical for assessing the safety condition of the structure. In the context of a few available accelerometers, this paper proposes a novel time-varying external force identification method using group sparse regularization based on the prior knowledge in the redundant dictionary. Firstly, the relationship between time-varying external force and acceleration responses is established, and a redundant dictionary is designed to create a sparse expression of external force. Then, the relevance of atoms in the redundant dictionary is revealed, and this prior knowledge is used to determine the group structures of atoms. As a result, a force identification governing equation is formulated, and the group sparse regularization is reasonably introduced to ensure the accuracy of the identified results. The contribution of this paper is that the group structures of atoms are reasonably determined based on prior knowledge, and the complexity in the process for identifying external force from measured acceleration responses is reduced. Finally, the effectiveness of the proposed method is demonstrated by numerical simulations and an experimental structure. The illustrated results show that, compared with the force identification method based on the standard l1-norm regularization, the proposed method can further improve the identified accuracy of unknown external force and greatly enhance the computational efficiency for the force identification problem. Full article
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