Advances in Fault Diagnosis, Defect Detection and Predictive Maintenance of Railway Vehicle Systems
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: 31 October 2025 | Viewed by 34
Special Issue Editors
Interests: fault diagnosis; structural health monitoring; vibration, acoustics and ultrasound techniques; advanced signal processing; data analytics; artificial intelligence-based applications in railway
Interests: vision computing; optical and visual inspection techniques; image processing and object detection; machine learning; artificial intelligence applications in railway
Interests: multimodal measurements and fusion; vision computing; infrared, laser and visual techniques; intelligent transportation systems; artificial intelligence applications in railway
Special Issue Information
Dear Colleagues,
Railway vehicles, accounting for over 30% of freight and 10% of passenger transportation in a majority of countries, are developing rapidly and becoming one of the backbones of global transportation. Moreover, railway systems are essential for fostering the economic prosperity and sustainability of modern metropolitan areas, encompassing various operating modes such as high-speed railways, freight railways, urban railways and subways.
Typically, the running safety of railway systems suffers from potential hazards—both from the conditions of railway infrastructures and critical components of vehicles. This has attracted much attention in the research community in the past decade. With this, in order to ensure the safe operation of railways, a wide variety of sensing and measurement technologies have been utilized alongside advanced data analytics by the research community in the fault diagnosis and predictive maintenance of rolling stocks and related civil infrastructures.
This Special Issue, entitled ”Advances in Fault Diagnosis, Defect Detection and Predictive Maintenance of Railway Vehicle Systems”, aims to explore the latest research and state-of-the-art contributions in the fault diagnosis, prognosis, defect detection, condition monitoring and health assessment of infrastructures and key components of vehicles, i.e., axles, wheelsets, bearings and rail tracks. In this, it aims to provide solutions to difficulties in safety assurance, and yield insights in making the railway vehicle system more efficient, secure, reliable and sustainable.
This Special Issue invites original research papers that address the challenges and opportunities in the above fields. The potential topics include but are not limited to the following:
- Advanced sensing and inspection technologies of railway vehicle systems;
- Intelligent fault diagnosis and prognosis of railway vehicle systems;
- Multimodal fusion and condition monitoring of railway vehicle systems;
- Prognostic and health management of railway vehicle systems;
- Predictive maintenance strategy of railway vehicle systems;
- Signal/image processing and discriminative feature extraction in fault diagnosis;
- Application of data analytics and artificial intelligence in fault diagnosis;
- Structural health monitoring/management of vehicle components;
- Non-destructive testing and defect detection of vehicle components;
- Remaining-useful-life prediction of vehicle components.
Dr. Kangwei Wang
Dr. Jin Zhang
Prof. Dr. Cheng Wu
Guest Editors
Manuscript Submission Information
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Keywords
- fault diagnosis and prognosis
- advanced sensing and inspection technologies
- data analytics and artificial intelligence
- structural health monitoring/management
- predictive maintenance
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