Optimal residual subspace model for structural damage diagnosis: an approach independent of operational and environmental variations

2022 ◽  
Vol 12 (1) ◽  
pp. 44
Author(s):  
Kundan Kumar ◽  
Sumanshu Agarwal
Keyword(s):  
Structural Damage ◽  
Damage Diagnosis ◽  
Environmental Variations

scholarly journals Structural Damage Diagnosis and Prediction Using Machine Learning and Deep Learning Models: Comprehensive Review of Advances

2019 ◽  
Author(s):  
Amir Mosavi
Keyword(s):  
Machine Learning ◽  
Composite Structures ◽  
Structural Damage ◽  
Structural Integrity ◽  
State Of The Art ◽  
Future Trends ◽  
Learning Models ◽  
Damage Diagnosis ◽  
Comprehensive Review ◽  
Initiation And Propagation

The loss of integrity and adverse effect on mechanical properties can be concluded as attributing miro/macro-mechanics damage in structures, especially in composite structures. Damage as a progressive degradation of material continuity in engineering predictions for any aspects of initiation and propagation requires to be identified by a trustworthy mechanism to guarantee the safety of structures. Besides the materials design, structural integrity and health are usually prone to be monitored clearly. One of the most powerful methods for the detection of damage is machine learning (ML). This paper presents the state of the art of ML methods and their applications in structural damage and prediction. Popular ML methods are identified and the performance and future trends are discussed.

Structural Damage Diagnosis and Assessment under Seismic Excitations

2005 ◽  
Vol 131 (10) ◽  
pp. 1036-1045 ◽  
Author(s):  
Tian-Wei Ma ◽  
Henry T. Yang ◽  
Chih-Chen Chang
Keyword(s):  
Structural Damage ◽  
Seismic Excitations ◽  
Damage Diagnosis
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