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Machines
Special Issues
New Advances in Rotating Machinery
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New Advances in Rotating Machinery

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Machines Testing and Maintenance".

Deadline for manuscript submissions: 30 September 2024 | Viewed by 2748

Special Issue Editors

Prof. Dr. Jong-Myon Kim

E-Mail Website
Guest Editor
School of IT Convergence, University of Ulsan, Ulsan 4402, Republic of Korea
Interests: machine learning; signal processing; image processing; machine fault diagnosis and health prognosis; condition monitoring; deep learning; embedded systems
Special Issues, Collections and Topics in MDPI journals
Dr. Zahoor Ahmad

E-Mail Website
Guest Editor
Department of Electrical, Electronic, and Computer Engineering, University of Ulsan, Ulsan 4402, Republic of Korea
Interests: fault detection and diagnosis; signal processing; multiscale signal analysis; statistical and temporal signal analysis; signal to image conversion and analysis; artificial intelligence; explainable machine learning; feature engineering; big data; anomaly detection and pattern recognition; algorithms; data structures
Special Issues, Collections and Topics in MDPI journals
Dr. Akhand Rai

E-Mail Website
Guest Editor
School of Engineering and Applied Science, Ahmedabad University, Ahmedabad 380009, India
Interests: machine design; nonlinear dynamics and vibration analysis; condition monitoring; rotating machinery; rolling element bearings and gears; fault diagnosis; fault prognosis; pipeline leak diagnosis; mental stress detection; battery management and fault detection

Special Issue Information

Dear Colleagues,

Various types of rotating machinery are widely used in different industrial applications. The industry’s technological advancement demands advanced and more precise rotating machinery. To meet these demands, the construction complexity of the rotating machinery is increasing. Furthermore, these machines operate in harsh working conditions for a long session. As a result, different types of incipient faults may develop during their operation. The unrecognized occurrence and development of these faults in the rotating machines with high responsibility can lead to fatal failure and tragic consequences, including long downtime, costly repairs, economic losses, and compromised safety of the operating staff. To ensure the reliable and efficient operation of the machine, improvement in rotating machinery dynamics, rotating machine design, and the development of condition-based health management approaches based on vibration and acoustic emission evaluation are inevitable.

In recent years, the availability of data, computational power, and advances in artificial intelligence have allowed researchers to solve the enticing problem of efficient machine design and timely health management of rotating machinery.

This Special Issue is centered around cutting-edge research concerning the recent advances in health management for rotating machinery. Furthermore, review articles and research concerning recent advances in the design of rotating machinery are also encouraged.

Prof. Dr. Jong-Myon Kim
Dr. Zahoor Ahmad
Dr. Akhand Rai
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. Machines is an international peer-reviewed open access monthly 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 2400 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

  • rotating machinery
  • rotor dynamics
  • fault diagnosis
  • prognosis
  • artificial intelligence
  • modal analysis
  • signal processing
  • condition monitoring

Published Papers (2 papers)

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Research

0 pages, 7443 KiB  
Article
A Technique for Bearing Fault Diagnosis Using Novel Wavelet Packet Transform-Based Signal Representation and Informative Factor LDA
by Andrei S. Maliuk, Zahoor Ahmad and Jong-Myon Kim
Machines 2023, 11(12), 1080; https://doi.org/10.3390/machines11121080 - 11 Dec 2023
Viewed by 1158
Abstract
This paper proposes a new method for bearing fault diagnosis using wavelet packet transform (WPT)-based signal representation and informative factor linear discriminant analysis (IF-LDA). Time–frequency domain approaches for analyzing bearing vibration signals have gained wide acceptance due to their effectiveness in extracting information [...] Read more.
This paper proposes a new method for bearing fault diagnosis using wavelet packet transform (WPT)-based signal representation and informative factor linear discriminant analysis (IF-LDA). Time–frequency domain approaches for analyzing bearing vibration signals have gained wide acceptance due to their effectiveness in extracting information related to bearing health. WPT is a prominent method in this category, offering a balanced approach between short-time Fourier transform and empirical mode decomposition. However, the existing methods for bearing fault diagnosis often overlook the limitations of WPT regarding its dependence on the mother wavelet parameters for feature extraction. This work addresses this issue by introducing a novel signal representation method that employs WPT with a new rule for selecting the mother wavelet based on the power spectrum energy-to-entropy ratio of the reconstructed coefficients and a combination of the nodes from different WPT trees. Furthermore, an IF-LDA feature preprocessing technique is proposed, resulting in a highly sensitive set of features for bearing condition assessment. The k-nearest neighbors algorithm is employed as the classifier, and the proposed method is evaluated using datasets from Paderborn and Case Western Reserve universities. The performance of the proposed method demonstrates its effectiveness in bearing fault diagnosis, surpassing existing techniques in terms of fault identification and diagnosis performance. Full article
(This article belongs to the Special Issue New Advances in Rotating Machinery)
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18 pages, 6413 KiB  
Article
Modal Balancing of Warped Rotors without Trial Runs Using the Numerical Assembly Technique
by Georg Quinz, Gregor Überwimmer, Michael Klanner and Katrin Ellermann
Machines 2023, 11(12), 1073; https://doi.org/10.3390/machines11121073 - 07 Dec 2023
Viewed by 836
Abstract
The increasing use of high-speed machinery leads to a growing demand for efficient balancing methods for flexible rotors. Conventional balancing methods are costly and time-consuming since they require multiple trial runs. For this reason, recent research focuses on model-based balancing methods, which substitute [...] Read more.
The increasing use of high-speed machinery leads to a growing demand for efficient balancing methods for flexible rotors. Conventional balancing methods are costly and time-consuming since they require multiple trial runs. For this reason, recent research focuses on model-based balancing methods, which substitute measurements with simulations. This work presents and examines a model-based modal balancing method, which utilizes the Numerical Assembly Technique (NAT) for the in situ balancing of warped rotors with flexible behaviour. NAT is a successive modification of discrete–continuous modelling that leads to analytical harmonic solutions and is very computationally efficient. In this version of NAT, internal damping is also included with a viscoelastic material model using fractional time derivatives. The modal balancing procedure is adapted to handle measurements outside of the critical speeds and the effect of the pre-bend on the rotor. The accuracy of the simulations is shown by comparing measured mode shapes and eigenvalues with values calculated with NAT. Furthermore, the first two modes of a rotor test bed are successfully balanced without trial runs. Full article
(This article belongs to the Special Issue New Advances in Rotating Machinery)
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