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Lubricants
Special Issues
Condition Monitoring and Simulation Analysis of Bearings
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Condition Monitoring and Simulation Analysis of Bearings

A special issue of Lubricants (ISSN 2075-4442).

Deadline for manuscript submissions: closed (25 February 2024) | Viewed by 10562

Special Issue Editors

Dr. Zhiwei Wang

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Guest Editor
Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Southwest Jiaotong University, Chengdu 610031, Sichuan, China
Interests: condition monitoring and fault diagnosis; bearing and gear transmission dynamics
Dr. Yang Song

E-Mail Website
Guest Editor
Department of Built Environment, Oslo Metropolitan University, Oslo, Norway
Interests: pantograph-catenary interaction; railway; vehicle dynamics; current collection quality
Special Issues, Collections and Topics in MDPI journals
Dr. Ruichen Wang

E-Mail
Guest Editor
School of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
Interests: vehicle dynamics; energy harvesting; wheel–rail interface condition monitoring and inspection; mechanical system modeling; fault diagnosis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Bearings are widely used in aerospace, automotive, railway vehicle, ship, and other mechanical systems. The service status of bearings usually has an important impact on the operation safety of the above-mentioned mechanical systems. The condition monitoring and simulation analysis of bearings during operation are essential to ensure the operation safety of mechanical systems.

In the actual operation process, bearings are often subjected to the combined effect of internal and external excitations. How to accurately grasp the dynamic response and fault feature under such complex excitations and effectively carry out condition monitoring are the major challenges currently being faced. Solving this problem requires innovative approaches that combine theoretical foundations such as tribology, dynamics, and signal processing.

The aim of this Special Issue is to share advances in the topic of dynamics modeling, simulation analysis, condition monitoring, signal processing, and other related novel aspects in the field of roller-and sliding bearings. Both experimental and theoretical investigations are highly welcome

Dr. Zhiwei Wang
Dr. Yang Song
Dr. Ruichen Wang
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. Lubricants 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 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

  • bearing
  • signal processing
  • fault diagnosis
  • monitoring technology
  • modeling and simulation
  • tribological analysis
  • dynamics analysis
  • fault features

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Published Papers (6 papers)

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Research

16 pages, 4241 KiB  
Article
Vibration-Based Detection of Axlebox Bearing Considering Inner and Outer Ring Raceway Defects
by Chuang Liu, Xinwen Zhang, Ruichen Wang, Qiang Guo and Junguo Li
Lubricants 2024, 12(5), 142; https://doi.org/10.3390/lubricants12050142 - 23 Apr 2024
Viewed by 1035
Abstract
The occurrence of an axlebox bearing ring raceway defect is an inevitable and commonly observed phenomenon in railway wheels. It not only leads to surface damage but also poses the potential threat of further damage and degradation, thereby increasing the risks associated with [...] Read more.
The occurrence of an axlebox bearing ring raceway defect is an inevitable and commonly observed phenomenon in railway wheels. It not only leads to surface damage but also poses the potential threat of further damage and degradation, thereby increasing the risks associated with running safety and maintenance costs. Hence, it becomes imperative to detect raceway defects at an early stage to mitigate safety hazards and reduce maintenance efforts. In this study, the focus lies in investigating the effectiveness of vibration-based detection techniques for identifying raceway defects in high-speed train axlebox bearing systems. To achieve this, a dynamic model that accurately represents the coupling dynamics between the vehicle and the track is developed. This model incorporates various dynamic factors, such as traction transmission, gear transmission, and track geometry irregularities. By using the comprehensive dynamic model, the dynamic responses of the axlebox can be accurately calculated. The proposed methodology primarily revolves around analysing the vertical vibrations of the axlebox caused by raceway defects in both the time and frequency domains. Additionally, an envelope analysis using a developed band-pass filter is also employed. The results obtained from this study clearly demonstrate the successful detection of raceway defects in a more realistic vehicle model, thereby providing an efficient approach for the detection of axlebox bearing raceway defects. Consequently, this research contributes significantly to the field of high-speed train systems and paves the way for enhanced safety and maintenance practices. Full article
(This article belongs to the Special Issue Condition Monitoring and Simulation Analysis of Bearings)
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21 pages, 15394 KiB  
Article
Research on the Relationship between Dynamic Characteristics and Friction Torque Fluctuation of CMGB under the Condition of Time-Varying Moment
by Wenhu Zhang, Shili Li, Gang Zhou, Ningning Zhou, Yan Zhao and Wanjia Li
Lubricants 2023, 11(12), 525; https://doi.org/10.3390/lubricants11120525 - 11 Dec 2023
Viewed by 1607
Abstract
In this paper, a dynamic simulation analysis model was established for CMGB (control moment gyroscope bearing) under the conditions of time-varying moment. The influences of the moment’s response time, axial preload, and working temperature on the dynamic characteristics and friction torque of CMGB [...] Read more.
In this paper, a dynamic simulation analysis model was established for CMGB (control moment gyroscope bearing) under the conditions of time-varying moment. The influences of the moment’s response time, axial preload, and working temperature on the dynamic characteristics and friction torque of CMGB were analyzed, and the relevant verification tests were conducted. The results show that the friction torque fluctuation of CMGB directly corresponds to the dynamic characteristics. The faster the response time of the time-varying moment, the larger the friction torque fluctuation of CMGB. The larger preload minimizes the difference in the ball’s loading state, which is the actual reason for reducing the friction torque fluctuation. Moreover, as the working temperature increases, the friction torque fluctuation of CMGB decreases. Full article
(This article belongs to the Special Issue Condition Monitoring and Simulation Analysis of Bearings)
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16 pages, 10380 KiB  
Article
A Contribution to Experimental Identification of Frequency-Dependent Dynamic Coefficients of Tilting-Pad Journal Bearings with Centered and Off-Centered Pivot
by Philipp Zemella, Daniel Vetter, Thomas Hagemann and Hubert Schwarze
Lubricants 2023, 11(10), 428; https://doi.org/10.3390/lubricants11100428 - 3 Oct 2023
Cited by 3 | Viewed by 1419
Abstract
Linearized dynamic bearing parameters and models are of essential interest for rotordynamic analyses in machine design. This paper experimentally studies the impact of pad preload and pivot offset on the frequency-dependent characteristics of dynamic stiffness (K) and damping coefficients (C) of a KC-model [...] Read more.
Linearized dynamic bearing parameters and models are of essential interest for rotordynamic analyses in machine design. This paper experimentally studies the impact of pad preload and pivot offset on the frequency-dependent characteristics of dynamic stiffness (K) and damping coefficients (C) of a KC-model for tilting-pad journal bearings. For this purpose, two four-pad test bearing configurations (preload m=0.17, pivot offset 0.5 and preload m=0.47, pivot offset 0.6) that differ highly with respect to the pad design parameters are investigated. Contributing effects on the results due to geometric differences are excluded as far as possible, as only one aligning ring and one pivot support design is used. The tests are conducted on a high-performance test rig for surface speeds up to 140 m/s and excitation frequencies of 500 Hz. Significant deviations between the two bearings are identified that generally match theoretically predicted differences and, therefore, contribute to the validation of dynamic bearing modeling. Full article
(This article belongs to the Special Issue Condition Monitoring and Simulation Analysis of Bearings)
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14 pages, 2974 KiB  
Article
Calculation of Dynamic Coefficients of Air Foil Journal Bearings Using Time-Domain Identification
by Guangshuo Feng, Bo Liu, Liuyuan Li and Yiben Zhang
Lubricants 2023, 11(7), 294; https://doi.org/10.3390/lubricants11070294 - 13 Jul 2023
Cited by 1 | Viewed by 1953
Abstract
Dynamic coefficients of a bearing are basic elements of rotor dynamics analysis. At present, there are still some issues in the calculation of the dynamic coefficient of air foil bearing. In this paper, the dynamic coefficients of the air foil bearing are calculated [...] Read more.
Dynamic coefficients of a bearing are basic elements of rotor dynamics analysis. At present, there are still some issues in the calculation of the dynamic coefficient of air foil bearing. In this paper, the dynamic coefficients of the air foil bearing are calculated by time-domain identification. This method does not need to linearize the system equations, so it is generally applicable to different models for air foil bearings. Using the established method, this paper verified the calculation results using the foil model with axial uniform deformation for the first time, and the influence of the foil model on the dynamic coefficients was studied. The calculation results of the foil models with axial uniform deformation and axial independent deformation have significant differences. Furthermore, the accuracy of the dynamic coefficient method for different disturbance amplitudes was compared. The results indicate that the dynamic coefficient method has good accuracy over a large disturbance range. Full article
(This article belongs to the Special Issue Condition Monitoring and Simulation Analysis of Bearings)
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17 pages, 5714 KiB  
Article
The Direct-Coupling Method for Analyzing the Performance of Aerostatic Bearings Considering the Fluid–Structure Interaction Effect
by Yangong Wu, Wentao Chen, Qinghui Zhang, Zheng Qiao and Bo Wang
Lubricants 2023, 11(3), 148; https://doi.org/10.3390/lubricants11030148 - 19 Mar 2023
Cited by 1 | Viewed by 1922
Abstract
In the interest of analyzing the effect of the structural deformation root caused by gas pressure on the static features of aerostatic bearings, a fluid–structure interaction (FSI) model based on orifice-type aerostatic bearings is proposed that can predict the characteristics of aerostatic bearings [...] Read more.
In the interest of analyzing the effect of the structural deformation root caused by gas pressure on the static features of aerostatic bearings, a fluid–structure interaction (FSI) model based on orifice-type aerostatic bearings is proposed that can predict the characteristics of aerostatic bearings more accurately by using the direct-coupling method (DCM). By using COMSOL Multiphysics, the governing equation matrix of the finite element model of structural deformation and gas film pressure was solved with the integral solution method, and the orifice boundary conditions were calculated with the root iteration method. At the same time, the static performance of I-shaped orifice-type aerostatic bearing with various supply pressures was analyzed theoretically and tested experimentally. The results show that in comparison with the calculation results without taking account of structural deformation, the theoretical values from the model derived in this paper considering the FSI effect are closer to the experimental values. Finally, by using the orthogonal design method, FSI simulation was carried out to analyze how the key dimension factors influence the structural stiffness of the spindle, and it is concluded that the thrust bearing’s stiffness is strongly influenced by the thickness of the thrust plate. Full article
(This article belongs to the Special Issue Condition Monitoring and Simulation Analysis of Bearings)
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23 pages, 5578 KiB  
Article
Research on Shaft Current Damage Identification of Variable Condition Motor Bearings Based on Multiscale Feature Label Propagation and Manifold Metric Transfer
by Guangbin Wang, Shubiao Zhao, Zhixian Zhong and Dong Zeng
Lubricants 2023, 11(2), 69; https://doi.org/10.3390/lubricants11020069 - 9 Feb 2023
Cited by 1 | Viewed by 1506
Abstract
The current damage is the most stubborn and difficult fault of high-power motor bearings because its vibration characteristics are easily confused with those of ordinary bearing mechanical faults. If it is discriminated as an ordinary mechanical fault without electrical insulation protection, the current [...] Read more.
The current damage is the most stubborn and difficult fault of high-power motor bearings because its vibration characteristics are easily confused with those of ordinary bearing mechanical faults. If it is discriminated as an ordinary mechanical fault without electrical insulation protection, the current damage of bearing shafts will still repeatedly appear. Aiming at the problem that it is difficult to identify the bearing current damage fault under variable working conditions, a bearing shaft current damage identification method based on multiscale feature label propagation and manifold metric transfer (MFLP-MMT) is proposed. Firstly, the multiscale sub-band signal is obtained by wavelet packet decomposition, and the multiscale sub-band fuzzy entropy is obtained by calculating its fuzzy entropy. Then, according to the extracted features, a neighbor graph is constructed on the source domain of the known fault label to obtain the pseudo label of the target domain sample, and the source domain label information is gradually diffused by way of the graph label propagation. The multiscale sub-band fuzzy entropy of the sample is mapped to the low-dimensional manifold space by locality preserving projections (LPP), and the source domain samples close to the target domain are given higher weights by cross-domain density ratio estimation to solve the problem of domain offset. Combined with the label samples of the target domain in label propagation, the manifold distance metric is learned to minimize the intra-class distance and maximize the inter-class distance in the domain and eliminate the overlapping phenomenon in the domain. By increasing the range of label propagation after each iteration, the label propagation error of the leading graph is gradually reduced, and unsupervised metric transfer learning is realized. The experimental results show that the new method is superior to the semi-supervised transfer learning method in fault identification ability; the highest fault identification accuracy can reach 100% and it has a good robustness. Full article
(This article belongs to the Special Issue Condition Monitoring and Simulation Analysis of Bearings)
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