Robust structural damage detection with deep multiple instance learning for sensor fault tolerance

Authors

Ruhua Wang (ORCID: https://orcid.org/0000-0001-5798-8118)
Ling Li (ORCID: https://orcid.org/0000-0001-9722-9503)
Senjian An (ORCID: https://orcid.org/0000-0002-1758-6824)
Hong Shun Hao (ORCID: https://orcid.org/0000-0001-7509-8653)
Bradley Ezard

Institutions

Shenzhen University (CN)
Curtin University (AU)
Guangzhou University (CN)
China Guangzhou Analysis and Testing Center (CN)

Publication Details

Journal: Engineering Structures
Published: 2025-03-05
DOI: https://doi.org/10.1016/j.engstruct.2025.119957
Citations: 2
Primary Topic: Structural Health Monitoring Techniques
Type: article
Field-Weighted Citation Impact: 1.91

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article

Robust structural damage detection with deep multiple instance learning for sensor fault tolerance

Ruhua Wang, Ling Li, Senjian An, Hong Shun Hao et al.

Mar 5, 2025

2 citations

Engineering Structures

Structural Health Monitoring Techniques

1.91

article

Robust structural damage detection with deep multiple instance learning for sensor fault tolerance

Ruhua Wang, Ling Li, Senjian An, Hong Shun Hao, Bradley Ezard

March 5, 2025article en

2 citations

Abstract

No abstract available for this paper.

Engineering StructuresVol. 331

Shenzhen University (CN), Curtin University (AU), Guangzhou University (CN), China Guangzhou Analysis and Testing Center (CN)

Climate action

Openalex Percentile: Top 17%

Structural Health Monitoring Techniques

1.91

DOI Open Access PDF OpenAlex

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Robust structural damage detection with deep multiple instance learning for sensor fault tolerance — Ruhua Wang, Ling Li, et al. · Engineering Structures (2025) | TGRS Research Map | TGRS