ArticlePloS one2025
Artificial intelligence-assisted method of structural health monitoring of subway shield tunnel based on insulation degradation location.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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2 citing papers in PubMed.
- Electrochemical noise-based data mining to environmental ClScientific reports · 2026Article
- Article
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3 authors.
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Abstract
Stray current leakages inevitably arise to seriously threaten the reliability of the subway tunnel structure and third-party system through electrochemical corrosion. Location of stray current leakage provides novel approach to mitigate stray current corrosion and valid guidance for maintenance of subway tunnel. The present study is dedicated to develop an integrated network-based method for locating the insulation degradation in subway tunnel. In this work, a predictive model based on LWQPSO-SOM algorithm is designed to cluster the risk level of stray current leakage through data mining. Then, an evaluation index Phigh is proposed to calculate the probability of high-risk index in the clustering results. Identification results of leakage zone of stray current is effectively validated through the measurement of rail-to-earth conductance. Results showed that the distribution of Phigh is highly related with rail-to-earth conductance distribution, indicating that the proposed method is applicable for stray current leakage location in the subway tunnel and potentially applicable in engineering fields.
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