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Applied Sciences
Special Issues
Recent Advances and Innovation in Prognostics and Health Management
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Recent Advances and Innovation in Prognostics and Health Management

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: 20 September 2024 | Viewed by 3083

Special Issue Editors

Dr. Di Liu

E-Mail Website
Guest Editor
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Interests: failure mechanism analysis; degradation modeling; reliability estimation; prognostics and health management
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Xingjian Wang

E-Mail Website
Guest Editor
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Interests: fault diagnosis; fault-tolerant control; reliability estimation; prognostics and health management
Dr. Cun Shi

E-Mail Website
Guest Editor
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Interests: prognostics and health management; performance degradation; nonlinear control for mechatronic systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Prognostics and Health Management (PHM) is a field that focuses on the degradation mechanisms of systems in order to estimate their health status, anticipate their failure and optimize their maintenance. PHM uses methods, tools and algorithms for monitoring, anomaly detection, cause diagnosis, prognosis of the remaining useful life (RUL) and maintenance optimization.

For the sake of high reliability, safety and supportability, modern equipment is usually equipped with PHM to realize reliable operation and health service. Hence, PHM has attracted a lot of attention and is a research focus in reliability engineering.

The purpose of this Special Issue is to show and share new ideas and achievements of PHM approaches, methods and related applications in engineering practices with relevant experts, scholars and engineers around the world. For this Special Issue, original research articles and reviews are welcome.

Topics and themes of this Special Issue may include but are not limited to:

  • degradation and failure mechanism analysis;
  • degradation modeling and related statistical methods;
  • fault and RUL prognostics;
  • maintenance strategy;
  • fault diagnosis and fault-tolerant control;
  • digital twins and machine learning techniques in PHM;
  • reliability estimation and risk analysis;
  • useful life evaluation.

Dr. Di Liu
Prof. Dr. Xingjian Wang
Dr. Cun Shi
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. Applied Sciences 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 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

  • prognostics and health management
  • failure mechanism analysis
  • degradation modeling
  • reliability estimation and prediction
  • fault diagnosis
  • fault-tolerant control
  • risk analysis
  • maintenance strategy
  • digital twins
  • machine learning

Published Papers (3 papers)

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Research

0 pages, 6089 KiB  
Article
Research on the Remaining Life Prediction Method of Rolling Bearings Based on Multi-Feature Fusion
by Guanwen Zhang and Dongnian Jiang
Appl. Sci. 2024, 14(3), 1294; https://0-doi-org.brum.beds.ac.uk/10.3390/app14031294 - 4 Feb 2024
Viewed by 791
Abstract
Rolling bearings are one of the most important and indispensable components of a mechanical system, and an accurate prediction of their remaining life is essential to ensuring the reliable operation of a mechanical system. In order to effectively utilize the large amount of [...] Read more.
Rolling bearings are one of the most important and indispensable components of a mechanical system, and an accurate prediction of their remaining life is essential to ensuring the reliable operation of a mechanical system. In order to effectively utilize the large amount of data collected simultaneously by multiple sensors during equipment monitoring and to solve the problem that global feature information cannot be fully extracted during the feature extraction process, this research presents a technique for forecasting the remaining lifespan of rolling bearings by integrating many features. Firstly, a parallel multi-branch feature learning network is constructed using TCN, LSTM, and Transformer, and a parallel multi-scale attention mechanism is designed to capture both local and global dependencies, enabling adaptive weighted fusing of output features from the three feature extractors. Secondly, the shallow features obtained by the parallel feature extractor are residually connected with the deep features through the attention mechanism to improve the efficiency of utilizing the information of the front and back features. Ultimately, the combined characteristics produce the forecasted findings for the RUL of the bearing using the fully connected layer, and RUL prediction studies were performed with the PHM 2012 bearing dataset and the XJTU-SY bearing accelerated life test dataset, and the experimental results demonstrate that the suggested method can effectively forecast the RUL of various types of bearings with reduced prediction errors. Full article
(This article belongs to the Special Issue Recent Advances and Innovation in Prognostics and Health Management)
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24 pages, 4104 KiB  
Article
Fault Mode Analysis and Convex Optimization-Based Fault-Tolerant Control for New Type Dissimilar Redundant Actuation System of Near Space Vehicle
by Jian Huang, Jun Wang, Weikang Li, Di Liu, Cun Shi and Fan Zhang
Appl. Sci. 2023, 13(23), 12567; https://0-doi-org.brum.beds.ac.uk/10.3390/app132312567 - 21 Nov 2023
Viewed by 712
Abstract
A new type dissimilar redundant actuation system (NT-DRAS), which is composed of an electro-hydrostatic actuator (EHA) and an electro-mechanical actuator (EMA), is applied in high value unmanned aerial vehicles such as the future near space vehicles to improve their reliability and performance index [...] Read more.
A new type dissimilar redundant actuation system (NT-DRAS), which is composed of an electro-hydrostatic actuator (EHA) and an electro-mechanical actuator (EMA), is applied in high value unmanned aerial vehicles such as the future near space vehicles to improve their reliability and performance index simultaneously. Further improvement in the flight safety is achieved with the fault-tolerant control (FTC) technique which deals with system faults. This paper proposes a novel convex optimization-based fault-tolerant control (CO-FTC) strategy for the NT-DRAS subject to gradual faults which are included in the state space representation of the system. A convex analysis-based treatment for system uncertainty caused by gradual faults is applied to determine the control gain matrix. The existence condition of the control gain matrix is optimized in the linear matrix inequality (LMI) form. Finally, the determined subsystems based on the novel technique is used to solve the modeled robust FTC problem. Case studies of NT-DRAS subject to different gradual faults have been accomplished to illustrate the FTC necessity for NT-DRAS. Furthermore, the effectiveness of the proposed CO-FTC strategy is validated by comparative analysis of the simulation results. Full article
(This article belongs to the Special Issue Recent Advances and Innovation in Prognostics and Health Management)
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18 pages, 6985 KiB  
Article
Research on Bowden Cable–Fabric Force Transfer System Based on Force/Displacement Compensation and Impedance Control
by Xin Li, Guanjun Ma and Donghao Wang
Appl. Sci. 2023, 13(21), 11766; https://0-doi-org.brum.beds.ac.uk/10.3390/app132111766 - 27 Oct 2023
Viewed by 855
Abstract
Bowden cable–fabric is a key force transfer device for flexible exoskeletons, and its precise control of force/displacement is a significant factor in the human–machine interaction of flexible exoskeletons. In this paper, a force/displacement control method based on friction compensation and impedance control was [...] Read more.
Bowden cable–fabric is a key force transfer device for flexible exoskeletons, and its precise control of force/displacement is a significant factor in the human–machine interaction of flexible exoskeletons. In this paper, a force/displacement control method based on friction compensation and impedance control was proposed based on a flexible Bowden cable–fabric force transfer testbed system. First, a set of in vitro experimental platforms simulating Bowden cable–fabric force transfer was built according to a typical flexible exoskeleton force transfer system, and following the walking gait of lower limbs, the expected force and knee joint motion were set. Secondly, the Bowden cable–fabric force transfer friction model was constructed as the basis of the system’s force transfer compensation. In addition, the stiffness model of Bowden cable–fabric and the lower leg movement model were established and combined with impedance control to realize the precise control of system displacement. Finally, the damping and stiffness parameters suitable for the system were obtained through the impedance control simulation. In terms of the experiment, an in vitro Bowden cable–fabric force transfer experimental platform was built, and the expected force with the input peak value of 40 N, 50 N, and 60 N was set. Through the friction and position compensation model of Bowden cable–fabric force transfer and impedance control, the relative root-mean-square errors of the output force and expected force were obtained as 2.53%, 2.16%, and 2.07%, respectively. Therefore, the effectiveness of the proposed method is verified, which provides a foundation for the engineering application of flexible exoskeletons. Full article
(This article belongs to the Special Issue Recent Advances and Innovation in Prognostics and Health Management)
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