A Review of Machine Learning Algorithms for vibration-based SHM and vision-based SHM

The rapid growth of population and expansion of urban cites within the limited land resources, provided the way for high-rise building construction. The research on Structural Health Monitoring (SHM) of high-rise buildings have been actively conducted. However, monitoring such tall structures for a...

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Bibliographic Details
Published in2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS) pp. 418 - 422
Main Authors Indhu, R., Sundar, G. Ram, Parveen, H. Summia
Format Conference Proceeding
LanguageEnglish
Published IEEE 23.02.2022
Subjects
Buildings
Inference algorithms
Learning (artificial intelligence)
Machine Learning (ML) Vibration based SHM
Machine learning algorithms
Prediction algorithms
Sociology
Structural Health Monitoring (SHM)
Vibrations
Vision based SHM
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Summary:The rapid growth of population and expansion of urban cites within the limited land resources, provided the way for high-rise building construction. The research on Structural Health Monitoring (SHM) of high-rise buildings have been actively conducted. However, monitoring such tall structures for a long term faces various difficulties. Therefore, Machine Learning algorithm applications in Structural Health Monitoring have overcome the difficulty in the monitoring of high-rise buildings. In this review, Machine Learning algorithm is categorized of two domains, they are vibration-based SHM and vision-based SHM. The usefulness of applying Machine Learning algorithms in Structural Health Monitoring i.e., for efficient damage identification and prediction have been outlined.
DOI:10.1109/ICAIS53314.2022.9742818