Demonstrates improved modeling accuracy and cognitive efficiency in railway settlement monitoring, indicating better maintenance decisions.
Railway track settlement is a common issue during long-term operations. Its uneven deformation not only disrupts the geometric continuity of the track but also affects ride quality and structural integrity. Existing monitoring methods rely on discrete measurement points and manual modeling workflows, resulting in low modeling efficiency and limited cognitive effectiveness of visualisation. To address these challenges, we propose a rule-constrained modeling and enhanced visualisation method for railway track settlement. First, a component-based expression is developed, considering the typical settlement characteristics of embankments, bridges, and tunnels. Settlement propagation formulas and component coordination constraints are integrated into BIM, enabling rule-constrained modeling and consistent representation. Second, key settlement areas are highlighted in large-scale 3D scenes using visual variables and rendering strategies, including color, transparency, and contour enhancement. A prototype system is implemented in MicroStation and validated in typical high-speed railway segments. Results show that the proposed method achieves over 96% modeling accuracy for all three structure types and significantly enhances user cognitive efficiency in eye-tracking experiments, reducing initial gaze time and improving task accuracy. This method provides effective technical support for railway settlement monitoring, risk identification, and maintenance decision-making.
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Xie et al. (2026) studied this question.
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