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Machines
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Remaining Useful Life Prediction for Rolling Element Bearings
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Remaining Useful Life Prediction for Rolling Element Bearings

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

Deadline for manuscript submissions: 31 May 2024 | Viewed by 3433

Special Issue Editor

Dr. David Isaac Ibarra-Zarate

E-Mail Website
Guest Editor
Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Ave. Eugenio Garza Sada 2501, Monterrey 64849, NL, Mexico
Interests: acoustics; acoustics and acoustic engineering; noise analysis; acoustic signal processing; acoustic analysis; wave propagation; vibration analysis; signal processing; audio signal processing; audio engineering

Special Issue Information

Dear Colleagues,

Industry 4.0 has transformed the business environment, from the increase in sensors and control systems to the development of new maintenance strategies, with data-based decision making being one of the most popular aspects. This type of maintenance aims to optimize the times of activities and is more efficient from an economic point of view compared to traditional methods, based on the times and similarities. Data-based maintenance increases system reliability by improving the useful life of machine components, allowing them to be repaired or replaced before a critical failure occurs that causes severe and costly problems. The most vulnerable components of rotating machines are bearings, and they are widely used in the manufacturing industry; most of the critical failures in industrial machinery occur due to the malfunction of these elements, to such an extent that by guaranteeing the correct operation of the bearings a safe and economical state of operation is generated during the production process. Bearings are one of the main sources of nonlinearity in systems formed by rotating machines, since they significantly affect their operation. This nonlinear behavior has led to the development of a wide range of techniques, both for monitoring and for maintenance, making it possible to guarantee the normal operation of a machine's bearings. In applications such as turbines and aircraft engines, the condition of these elements is paramount because a simple imperfection can cause critical problems and extremely dangerous as well as expensive results. In CNC machine tools, the progressive wear of bearings cannot be avoided and it is important to continuously monitor and diagnose in order to generate an accurate diagnosis of the condition of machinery.

Dr. David Isaac Ibarra-Zarate
Guest Editor

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

  • fault diagnostics
  • rolling element bearing
  • remaining useful life prediction
  • condition monitoring

Published Papers (2 papers)

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Research

21 pages, 4865 KiB  
Article
Digital Twin-Driven Remaining Useful Life Prediction for Rolling Element Bearing
by Quanbo Lu and Mei Li
Machines 2023, 11(7), 678; https://doi.org/10.3390/machines11070678 - 24 Jun 2023
Cited by 1 | Viewed by 1418
Abstract
Traditional methods for predicting remaining useful life (RUL) ignore the correlation between physical world data and virtual world data, leading to the low prediction accuracy of RUL and affecting the normal working of rolling element bearing (REB). To solve the above problem, we [...] Read more.
Traditional methods for predicting remaining useful life (RUL) ignore the correlation between physical world data and virtual world data, leading to the low prediction accuracy of RUL and affecting the normal working of rolling element bearing (REB). To solve the above problem, we propose a hybrid method based on digital twin (DT) and long short-term memory (LSTM). The hybrid method combines the high simulation capabilities of DT and the strong data processing capabilities of LSTM. Firstly, we develop a DT system for the life characteristics analysis of an REB. When the DT system is implemented, we can obtain the theoretical value of RUL. Then, the experimental data is used to train the LSTM model. The output of LSTM is the actual value of RUL. Finally, the particle swarm optimization (PSO) algorithm fuses the theoretical values of DT with the actual values of LSTM. The case study demonstrates that the prediction accuracy of the hybrid method is greater than 97.5%, which improves the prediction performance and robustness of RUL. Therefore, the hybrid method is an important technology of REB prediction and health management (PHM). It realizes the early intervention and maintenance of mechanical equipment and ensures the safety of enterprises’ production. Full article
(This article belongs to the Special Issue Remaining Useful Life Prediction for Rolling Element Bearings)
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22 pages, 4015 KiB  
Article
Dynamics Modeling and Analysis of Rolling Bearings Variable Stiffness System with Local Faults
by Baoliang Guo, Wenlong Wu, Jianxiao Zheng, Yumin He and Jinhua Zhang
Machines 2023, 11(6), 609; https://doi.org/10.3390/machines11060609 - 02 Jun 2023
Viewed by 1191
Abstract
By analyzing the support of load-carrying rolling elements when the rolling elements fall into the fault position, the dynamics model of a rolling bearing variable stiffness system with local faults is proposed, considering the retention factor of the contact deformation. Then, this paper [...] Read more.
By analyzing the support of load-carrying rolling elements when the rolling elements fall into the fault position, the dynamics model of a rolling bearing variable stiffness system with local faults is proposed, considering the retention factor of the contact deformation. Then, this paper researches the change of effective contact stiffness, contact deformation, contact force, and the total effective stiffness of the rolling elements. The results show that the contact stiffness of the rolling elements abruptly decreases when the rolling elements fall into the fault position. The contact deformation and contact force of the load-carrying rolling elements in the load zone increase, rebalancing the external radial load while causing a sudden reduction in the total effective stiffness, resulting in the vibration of the system. When different rolling elements fall into the outer ring fault position, the change in total effective stiffness and the system response are equal in magnitude. Additionally, there is a significant outer race fault characteristic frequency accompanied by frequency multiplication in the fault characteristic spectrums. When different rolling elements fall into the inner race fault position, the total effective stiffness is modulated by the inner race rotation and varies dramatically, resulting in the amplitude of the system time domain vibration response also being modulated by the inner race rotation and varying dramatically. Additionally, there is a significant inner race rotational frequency accompanied by frequency multiplication, an inner race fault characteristic frequency accompanied by frequency multiplication, and a side frequency in the fault characteristic spectrums. The research can provide some reference for the effective diagnosis of the rolling bearing fault. Full article
(This article belongs to the Special Issue Remaining Useful Life Prediction for Rolling Element Bearings)
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