• Railway safety monitoring detection and maintenance technology and equipment
  • Railway safety monitoring detection and maintenance technology and equipment
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Railway safety monitoring detection and maintenance technology and equipment

Technologies and equipment that monitor the condition of tracks, bridges, tunnels, and trains in real-time to provide early warnings and enable predictive maintenance, preventing accidents and ensuring safety.

    (I) Holographic Intelligent Perception, Diagnosis and Health Management of Train Service Status

    In the future, the focus will be on the blind source analysis, feature selection and high-dimensional processing of non-stationary random signals from monitored objects to obtain effective information throughout the entire service status process. Researches will be conducted on the following aspects: methods for fault signal reconstruction from cyclostationary random monitoring data and intelligent diagnosis of early weak faults based on spectral correlation and entropy correlation; methods for predicting and early warning of equipment performance degradation based on adaptive random process prediction and machine learning; and methods for intelligent detection of wear and anomalies in key components based on 3D images and deep learning. Meanwhile, exploration will be made into the health index and predictive analysis algorithms for high-speed train systems, and the construction of a system polymorphic network reliability model and real-time reliability calculation method based on complex coupled networks, so as to form a comprehensive assessment and early warning scheme for the health status of train systems driven by both model and data.

     

    (II) Risk Perception and Dynamic Analysis of Train Operation Environment in Air-Space-Vehicle-Ground Integration

    Key researches will be carried out on the integrity detection technology of high-speed railway engineering, power supply and distribution infrastructure under the air-space-vehicle-ground integration framework, and exploration will be made into the all-weather three-dimensional perception data fusion method for engineering, power supply and distribution infrastructure along railways. An intelligent recognition model for small-target defects in infrastructure based on deep learning will be developed; methods for analyzing, predicting and early warning of infrastructure safety risk status will be established; and a dynamic risk analysis and assessment model for railway operation under the influence of disaster-causing factors in different operating environments will be constructed. In addition, researches will be conducted on the analysis model for risk generation and propagation of railway systems under environmental disasters based on complex network theory, so as to form the collaborative computing of railway operation environment status, cross-scale fusion risk assessment and collaborative decision-making technology based on the "terminal-edge-cloud" architecture.

     

    (III) Intelligent Risk Management and Control of Railway Operation in Large-Scale Road Networks

    Exploration will be made into the condition-based predictive maintenance method for single components of trains; an optimized model for the integrated strategy of condition-and-correlation-based preventive opportunity maintenance for multi-components will be constructed; and a fast solution algorithm for on-line maintenance optimization of multi-components will be developed. Researches will be conducted on maintenance decision support technology based on virtual reality and digital twin; a model for analyzing the impact of train operation risks under emergency situations will be established; and a safety command and dispatch model under emergency situations based on train operation risk prediction will be constructed. Meanwhile, exploration will be made into the optimized method for generating flexible train fleet operation plans considering emergency situations, so as to form an optimized scheme for collaborative dispatch of train fleets in regional road networks under large-scale emergency scenarios.


    FAQ‍‌‍‍‌‍‌‍‍‌-‍‌‍‍‌ Frequently Asked Questions

    1. When and where will the Expo be held?

    The Expo is scheduled to be at the Xiamen International Conference and Exhibition Center (XICEC), Hall C, Xiamen, China, from May 13 to 15, 2026.

    2. What is the exhibition scale?

    The event covers an area of 40,000 m² with more than 350 companies. The number of professional visitors is expected to be over 30,000 from all around the globe.

    3. What activities are included?

    There will be more than 80 professional forums and events discussing various topics like smart mobility, transportation communication, safety, and sustainable development.

    4. How many countries and regions are involved?

    The delegation is made up of the members from more than 80 countries and regions, so it is a worldwide meeting of intelligent transportation innovation.

    5. Are there opportunities for cooperation?

    Without a doubt. As an event of over 1,000 global partners, the Expo is full of opportunities for business collaboration, technology exchange, and investment.

    6. Who can I contact for details?

    If you want more information, please get in touch with the Organizing Committee via the official website's Contact Us ‍‌‍‍‌section. It is our pleasure to help ‍‌‍‍‌‍‌‍‍‌you.


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