High-Speed Train Control Risk Analysis Using Manifold State Models
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Solution Overview
Problem
Current dynamic analysis methods for high-speed train control systems are inefficient in real-time monitoring and predicting safety risks due to the complexity of the systems, leading to high computational resource requirements and inadequate real-time safety information for decision-makers.
Innovation Solution
A dynamic analysis method using a cusp manifold surface to determine the system running state and an elliptical umbilical manifold surface for safety risk calculation, allowing for real-time evaluation of safety indicators and risk indicators through the integration of DE, DB, and DS variables, enabling effective identification of safety or danger states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If state transit models (Markov chain, Petri net, dynamic fault tree) are used to dynamically describe safety state changes, then the system can output changes in safety risks, but the model size becomes extremely large and consumes very large online computing resources
Solution Approach 1:
The patent segments the complex state transit model into two separate manifold surfaces: a cusp manifold surface for system state discrimination and an elliptical umbilical manifold surface for safety risk calculation. This segmentation divides the originally monolithic complex model into modular components, each handling a specific aspect of safety analysis, thereby reducing overall model complexity and computational burden while maintaining comprehensive safety monitoring capability
Solution Approach 2:
The patent transitions from traditional state-based modeling to a geometric manifold-based approach, introducing new dimensional representations. The cusp manifold surface uses control variables (DE, DB) and state variable (DS) to create a three-dimensional safety state space, while the elliptical umbilical manifold adds another layer for risk calculation. This dimensional transformation enables more efficient representation of safety states compared to exhaustive state transit modeling
2Measurement precision
If comprehensive safety analysis is performed in real-time during high-speed running, then accurate safety state information is provided for decision-making, but computational resources are excessively consumed
Solution Approach 1:
The patent extracts only the essential features needed for safety assessment from the complex system state, representing them through controlled variables (DE - degree of risk of accumulated error, DB - degree of barrier of accumulated grid) and state variable (DS - degree of systematic safety). This extraction focuses computational effort on critical safety parameters rather than processing all possible system states, reducing computational resource consumption while maintaining measurement precision
Solution Approach 2:
The patent changes the parameters used for safety analysis from traditional state-based parameters to geometric manifold parameters. By representing safety states as positions on manifold surfaces rather than discrete states in a state transition model, the system achieves continuous real-time monitoring with reduced computational complexity, enabling efficient real-time parameter updates without exhaustive state enumeration
Data Source
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AI summary
A dynamic analysis method of the running safety risks of a high-speed train running control system is disclosed by the present invention, comprising: Step 1: constructing a system running state discriminating model based on a cusp manifold surface; Step 2: determining the system running state; Step 3: constructing a safety risk calculating model based on an elliptical umbilical manifold surface; Step 4: outputting changes in running safety indicators and running risk indicators. Compared with the prior art, the present invention can support the on-board computer to realize an accurate calculation of the train running safety risk.