On risk-based active learning for structural health monitoring-Reference-Cited by-同舟云学术

On risk-based active learning for structural health monitoring

Published:2022-03 Issue: Volume:167 Page:108569
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Hughes A.J.^ORCID,Bull L.A.^ORCID,Gardner P.^ORCID,Barthorpe R.J.,Dervilis N.,Worden K.

Funder

Engineering and Physical Sciences Research Council

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference34 articles.

1. Structural Health Monitoring: A Machine Learning Perspective;Farrar,2013

2. A probabilistic risk-based decision framework for structural health monitoring;Hughes;Mech. Syst. Signal Process.,2021

3. Probabilistic Risk Analysis: Foundations and Methods;Bedford,2001

4. A forward model driven structural health monitoring paradigm: Damage detection;Barthorpe,2021

5. Foundations of population-based SHM, Part III: Heterogeneous populations – mapping and transfer;Gardner;Mech. Syst. Signal Process.,2021

Cited by 25 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Canonical-correlation-based fast feature selection for structural health monitoring;Mechanical Systems and Signal Processing;2025-01

2. Advanced informatic technologies for intelligent construction: A review;Engineering Applications of Artificial Intelligence;2024-11

3. Application of a data-driven approach for maximum fatigue damage prediction of an unbonded flexible riser;Ocean Engineering;2024-08

4. An efficient active learning Kriging approach for expected fatigue damage assessment applied to wind turbine structures;Ocean Engineering;2024-08

5. On the data quality and imbalance in machine learning-based design and manufacturing—A systematic review;Engineering;2024-07