Guest Editors
Prof. Guoqing Jing, Beijing Jiaotong University, China
Email: gqjing@bjtu.edu.cn
Dr. Mohammad Siahkouhi, Western Sydney University, Australia
Email: m.siahkouhi@westernsydney.edu.au
Ms. Ran Zhang, University College Cork, Ireland
Email: ranzhang@ucc.ie
Summary
This special issue focuses on the critical area of railway infrastructure health monitoring and inspection, with a specific emphasis on integrating new technologies and sustainable monitoring practices, such as AI, drone, GPR, cloud point, smart self-sensing concrete etc. The goal is to address the challenges associated with ensuring the safety, efficiency, and longevity of railway tracks monitoring system through innovative approaches.
This special issue aims to explore and implement advanced sensing technologies to monitor the health and condition of various components of railway infrastructure, including tracks, bridges, transition zones and tunnels. This will involve the utilization of cutting-edge techniques such as different types of sensors, wireless sensor networks, and remote monitoring systems. The new technologies which offer the potential for continuous monitoring, enabling real-time data collection, early detection of structural issues, and proactive maintenance interventions.
In addition to the adoption of new technologies, the proposal underscores the importance of sustainable monitoring practices. The research will assess the environmental impact, energy efficiency, and cost-effectiveness of the monitoring systems. It will explore sustainable monitoring techniques such as self-powering sensors, energy harvesting systems, and optimized data analysis algorithms. By incorporating sustainability considerations, developing monitoring approaches that not only ensure the health of railway infrastructure but also minimize environmental impact and resource consumption.
Through the convergence of new technologies and sustainable monitoring strategies, this special issue seeks to contribute to the advancement of reliable and environmentally conscious railway infrastructure health monitoring practices. By enhancing safety, reliability, and sustainability, this special issue has the potential to significantly benefit railway networks and the communities they serve.
Therefore, the research topic aims to cover original articles or review articles that explore innovations in structural health monitoring (SHM) of railway infrastructures based on innovative.
The special issue is intended to include but not be limited to the following:
· Smart sensors and monitoring methods including Lidar; GPR; Smart self-sensing concrete and etc.
· Remote monitoring using InSAR, DIC and etc.
· Dynamic and static behavior analysis of railway components based on monitoring system data
· Application of AI, drone, robot, GPR, TLS and new technologies in railway SHM
· Sensor network and large scale sensor deployment monitoring methods
· Health an damage assessment
· Inversion of structural parameters based on monitoring information
Keywords
Railway Infrastructure; AI; Health Monitoring; Inspection and evaluation; Lidar; GPR; Smart self-sensing concrete
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