About this Research Topic
The emerging risks of aging railway infrastructure systems mainly rely on the lack of early warnings. This would allow asset maintainers the prioritization of critical components as well as a timely management. Therefore, an integrated research approach is critically needed in order to reinforce asset condition monitoring (bottom-up) and response prediction (top-down) of rail systems management, maintenance and operation in order to provide safe and seamless railways. Novel smart sensors, wireless technologies, and on-board monitoring technology such as infrastructure-to-infrastructure and infrastructure-to-vehicle communications are essential to modernize railway infrastructure systems. Integration of sensors in railway information model (RIM) will revolutionize real-time asset maintenance, monitoring and prioritization policy. The collaborative research focusing on health and condition monitoring will assure public safety and reliability. This Research Topic will pave the impact to railway industry through the benefit from knowledge transfer and technology establishment in this research field.
The second volume of this Research Topic will continue bringing together the research and innovation associated with rail infrastructure systems issues related to advanced condition monitoring. It is important to note that the rail transport system consists of interaction between inspection/monitoring, operation and maintenance. One of the important considerations is the flow of health condition data, which is often directed to passenger safety, overlooking the freight transport needs for cost saving. In the case of advanced condition monitoring can play an important role in providing novel methodological approaches optimizing reliability, availability and asset management. Therefore, systems consideration of rail infrastructure systems and the resulting impact at the systems level is welcome for this Research Topic.
Potential themes include but are not limited to the following:
• Advanced sensors
• Condition monitoring
• Advanced materials
• Non-destructive testing and evaluation
• Integrated intelligence
• Machine learning
• Asset management
• Maintenance and inspections
• Serviceability and optimization
• Big data analytics
• Rolling stocks
• Railway tracks
• Accident analysis
Keywords: Advanced Condition Monitoring, Railway Systems, Infrastructure Systems, Rolling Stocks, Advanced Sensors
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.