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New Trends in Fault Diagnosis of Marine Mechanical Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: 20 May 2026 | Viewed by 64

Special Issue Editors

School of Marine Science and Technology, Northwestern Polytechnical University, Xian 710072, China
Interests: intelligent monitoring technology for equipment status; fault diagnosis
Liverpool Logistics, Offshore and Marine Research Institute, Liverpool John Moores University, Liverpool L3 2AJ, UK
Interests: maritime traffic; uncertainty modeling; machine learning and intelligent solutions for reliability and safety technologies

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Guest Editor
Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico, University of Lisbon, 1049-001 Lisbon, Portugal
Interests: optimization and sustainable development of offshore aquaculture systems; long-term monitoring and fault diagnosis of offshore platforms; application of artificial intelligence in offshore structures
Department of Civil and Environmental Engineering, University of Liverpool, Liverpool L69 7ZX, UK
Interests: fault diagnostics, prognostics, and intelligent solutions; reliability and safety technologies for mechanical systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to invite you to contribute to this Special Issue, which focuses on the critical role of mechanical fault diagnosis in ensuring the reliability, efficiency, and safety of industrial and transportation systems. In an era marked by digital transformation and increasing system complexity, the demand for intelligent and proactive fault detection approaches has become more urgent than ever. This Special Issue aims to highlight the latest advancements in methodologies, technologies, and applications that are shaping the future of fault diagnosis across a wide range of mechanical systems, including those in manufacturing, energy, automotive, and maritime sectors.

Modern mechanical systems are increasingly integrated with sensing technologies, data acquisition platforms, and AI-based analytics, enabling real-time monitoring, predictive maintenance, and automated decision-making. The development of these intelligent diagnostic solutions is essential to reducing unplanned downtime, preventing catastrophic failures, and improving lifecycle performance. In particular, the maritime transportation industry—characterized by harsh operational environments, extended asset life cycles, and high safety requirements—offers unique challenges and opportunities for mechanical fault diagnosis.

With the advent of Industry 4.0 and the evolution toward more human-centric and resilient operations under Industry 5.0, this Special Issue aims to capture the interdisciplinary nature of fault diagnosis and its critical role in sustainable engineering practice. We invite researchers and practitioners to submit high-quality contributions that advance this field and offer actionable insights for complex mechanical systems.

This Special Issue welcomes original research articles and reviews that address both theoretical developments and practical implementations of fault diagnosis techniques. Topics of interest include, but are not limited to, the following:

  • Advanced signal processing and feature extraction for anomaly detection and fault diagnosis.
  • Machine learning and deep learning approaches in mechanical diagnosis.
  • Physics-informed and hybrid diagnostic models.
  • Digital twins and IoT-enabled diagnostics for mechanical systems.
  • Applications in maritime transportation, including ship propulsion and onboard machinery.
  • Condition-based and predictive maintenance strategies.
  • Uncertainty modeling and decision support in fault diagnosis.
  • Large models for prognostics and health management.

We look forward to receiving your valuable contributions that advance the understanding and application of the future mechanical fault diagnosis in industrial systems.

Dr. Dawei Gao
Dr. Hao Rong
Dr. Zhongchi Liu
Dr. Zifei Xu
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

  • fault diagnosis
  • predictive maintenance
  • maritime machinery monitoring
  • digital twin
  • advanced machine learning
  • signal processing
  • anomaly detection
  • intelligent reliability technologies

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Published Papers

This special issue is now open for submission.
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