State-of-the-art review on advancements of data mining in structural health monitoring
To date, data mining (DM) techniques, ie artificial intelligence, machine learning, and
statistical methods have been utilized in a remarkable number of structural health monitoring …
statistical methods have been utilized in a remarkable number of structural health monitoring …
A framework of structural damage detection for civil structures using fast fourier transform and deep convolutional neural networks
Y He, H Chen, D Liu, L Zhang - Applied Sciences, 2021 - mdpi.com
In the field of structural health monitoring (SHM), vibration-based structural damage
detection is an important technology to ensure the safety of civil structures. By taking …
detection is an important technology to ensure the safety of civil structures. By taking …
Current and future role of data fusion and machine learning in infrastructure health monitoring
Rapid advances in infrastructure health monitoring and sensing technologies allow the
monitoring of infrastructure assets continuously and in real-time throughout their life span …
monitoring of infrastructure assets continuously and in real-time throughout their life span …
[HTML][HTML] Comparative study of a newly proposed machine learning classification to detect damage occurrence in structures
Over the past two decades, an increasing number of large-scale structures have been built
around the world. Constructing these structures has been a time consuming and highly …
around the world. Constructing these structures has been a time consuming and highly …
Disjoint and functional principal component analysis for infected cases and deaths due to COVID-19 in South American countries with sensor-related data
C Martin-Barreiro, JA Ramirez-Figueroa, X Cabezas… - Sensors, 2021 - mdpi.com
In this paper, we group South American countries based on the number of infected cases
and deaths due to COVID-19. The countries considered are: Argentina, Bolivia, Brazil, Chile …
and deaths due to COVID-19. The countries considered are: Argentina, Bolivia, Brazil, Chile …
A novel CNN-LSTM hybrid model for prediction of electro-mechanical impedance signal based bond strength monitoring
The recent application of deep learning for structural health monitoring systems for damage
detection has potential for improvised structure performance and maintenance for long term …
detection has potential for improvised structure performance and maintenance for long term …
Unsupervised damage detection for offshore jacket wind turbine foundations based on an autoencoder neural network
Structural health monitoring for offshore wind turbine foundations is paramount to the further
development of offshore fixed wind farms. At present time there are a limited number of …
development of offshore fixed wind farms. At present time there are a limited number of …
A novel structural damage identification method using a hybrid deep learning framework
Y He, Z Huang, D Liu, L Zhang, Y Liu - Buildings, 2022 - mdpi.com
In the past few years, structural health monitoring (SHM) has become an important
technology to ensure the safety of structures. Structural damage identification methods …
technology to ensure the safety of structures. Structural damage identification methods …
Siamese neural networks for damage detection and diagnosis of jacket-type offshore wind turbine platforms
Offshore wind energy is increasingly being realized at deeper ocean depths where jacket
foundations are now the greatest choice for dealing with the hostile environment. The …
foundations are now the greatest choice for dealing with the hostile environment. The …
Estimation of combustion parameters from engine vibrations based on discrete wavelet transform and gradient boosting
An optimal control of the combustion process of an engine ensures lower emissions and fuel
consumption plus high efficiencies. Combustion parameters such as the peak firing pressure …
consumption plus high efficiencies. Combustion parameters such as the peak firing pressure …