JOURNAL ARTICLE

Health assessment of TBM diversion tunnel structure based on AHP and AMV models.

  • Published In: Journal of Intelligent & Fuzzy Systems, 2025, v. 48, n. 3. P. 305 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Zhang, Jianwei; Chen, Lei; Hou, Ge; Huang, Jinlin; Wang, Yong 3 of 3

Abstract

This article focuses on the structural health evaluation of Tunnel Boring Machine (TBM) diversion tunnels, proposing a comprehensive assessment method based on the Analytic Hierarchy Process-Matter Element Extension-Variable Weight Theory (AMV). Using monitoring data from a TBM diversion tunnel project in Guangdong Province, the study establishes a health evaluation index system incorporating 12 indicators related to structural response, durability, and external factors. The AMV method integrates variable weights derived from real-time data, improving upon the fixed weights of traditional AHP by more accurately reflecting indicator sensitivities and health status fluctuations. Results indicate that the tunnel’s structural health is at a basic safety level (grade B), with key sensitive indicators identified as segment settlement, opening, misalignment, and cracks, which should be prioritized in ongoing monitoring and maintenance. The study suggests that the AMV approach offers enhanced accuracy and practical value for health assessments of diversion tunnels and potentially other engineering structures.

Additional Information

  • Source:Journal of Intelligent & Fuzzy Systems. 2025/03, Vol. 48, Issue 3, p305
  • Document Type:Article
  • Subject Area:Power and Energy
  • Publication Date:2025
  • ISSN:1064-1246
  • DOI:10.3233/JIFS-239155
  • Accession Number:184162083
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