An intelligent railway operation and maintenance management approach based on BIM and semantic web
The building information modeling(BIM)technology plays a crucial role in enhancing the efficiency of railway operation and maintenance management.However,the heterogeneity of data generated from various inspection and maintenance activities,coupled with the complex spatiotemporal relationships,hinder the process of BIM data interpretation and integration.To address this challenge,a railway maintenance ontology(TOMO)based on the industry foundation classes(IFC)and semantic Web technology was developed.TOMO served three main functions:① Simplifying BIM model information based on railway maintenance lifecycle requirements.② Introducing mapping rules and establishing data extraction and transformation modules to integrate heterogeneous data from multiple sources,structurally defining complex spatiotemporal relationships between data.③ Combining data-driven techniques to study intelligent optimization methods for railway fine-tuning,providing flexible decision support.Finally,using static inspection data from a high-speed railway as an example,the effectiveness and practicality of this framework were verified.This framework held practical engineering significance in promoting data interoperability in the field,reducing the labor intensity of maintenance personnel,and enhancing the intelligence of maintenance management.
building information modelingoperation and maintenance managementsemantic web technologydata-drivenflexible decision