Real-time structural health monitoring based on measured and simulated data

被引：0

作者：

Long, Yanze ^{[1
]}

Chu, Shaoyang ^{[2
]}

Zhang, Ke ^{[2
,3
]}

Zhou, Peng ^{[1
]}

Shi, Huaitao ^{[2
]}

Hu, Tianqiang ^{[2
]}

机构：

[1] Shenyang Jianzhu Univ, Coll Engn Training & Innovat, Shenyang, Liaoning, Peoples R China

[2] Shenyang Jianzhu Univ, Sch Mech Engn, Shenyang, Liaoning, Peoples R China

[3] Shenyang Univ Technol, Sch Mech Engn, Shenyang, Liaoning, Peoples R China

来源：

NONDESTRUCTIVE TESTING AND EVALUATION | 2025年

关键词：

Digital twin; health monitoring; numerical model; surrogate model; SURROGATE MODEL; OPTIMIZATION;

D O I：

10.1080/10589759.2025.2487578

中图分类号：

TB3 [工程材料学];

学科分类号：

0805 ; 080502 ;

摘要：

Structural failure in Structural Health Monitoring (SHM) is often caused by overloading or incomplete inspections. This study developed an accurate and real-time digital twin model by utilising a Multi-fidelity Surrogate (MFS) model to integrate measured and simulated data. This approach effectively reduces resource consumption, improves monitoring accuracy, and enables comprehensive real-time health monitoring of a structure using live sensor data. Finally, the effectiveness of this method was validated through experimental case studies.

引用

页数：17

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