Vibration feature extraction using signal processing techniques for structural health monitoring: A review
Structural health monitoring (SHM) has become an important and hot topic for decades in
various fields of civil, mechanical, automotive, and aerospace engineering, etc. Estimating …
various fields of civil, mechanical, automotive, and aerospace engineering, etc. Estimating …
Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights
Conventional damage detection techniques are gradually being replaced by state-of-the-art
smart monitoring and decision-making solutions. Near real-time and online damage …
smart monitoring and decision-making solutions. Near real-time and online damage …
Data-driven structural health monitoring and damage detection through deep learning: State-of-the-art review
Data-driven methods in structural health monitoring (SHM) is gaining popularity due to
recent technological advancements in sensors, as well as high-speed internet and cloud …
recent technological advancements in sensors, as well as high-speed internet and cloud …
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 …
Mutual information based anomaly detection of monitoring data with attention mechanism and residual learning
Due to the damage of sensors or transmission equipment, abnormal monitoring data
inevitably exists in the measured raw data, and it significantly impacts the condition …
inevitably exists in the measured raw data, and it significantly impacts the condition …
A review of machine learning methods applied to structural dynamics and vibroacoustic
Abstract The use of Machine Learning (ML) has rapidly spread across several fields of
applied sciences, having encountered many applications in Structural Dynamics and …
applied sciences, having encountered many applications in Structural Dynamics and …
Deep learning-based procedure for structural design of cold-formed steel channel sections with edge-stiffened and un-stiffened holes under axial compression
This paper proposes a framework of deep belief network (DBN) for studying the structural
performance of cold-formed steel (CFS) channel sections with edge-stiffened/un-stiffened …
performance of cold-formed steel (CFS) channel sections with edge-stiffened/un-stiffened …
Deep learning-based axial capacity prediction for cold-formed steel channel sections using Deep Belief Network
In this study, a deep learning-based axial capacity prediction for cold-formed steel channel
sections is developed using Deep Belief Network (DBN). A total of 10,500 data points for …
sections is developed using Deep Belief Network (DBN). A total of 10,500 data points for …
Practical implementation of structural health monitoring in multi-story buildings
A Sivasuriyan, DS Vijayan, W Górski, Ł Wodzyński… - Buildings, 2021 - mdpi.com
This study investigated operational and structural health monitoring (SHM) as well as
damage evaluations for building structures. The study involved damage detection and the …
damage evaluations for building structures. The study involved damage detection and the …
Developing a heterogeneous ensemble learning framework to evaluate Alkali-silica reaction damage in concrete using acoustic emission signals
The monitoring and evaluation of Alkali-silica reaction (ASR) damage in concrete structures
are required to ensure the serviceability and integrity of concrete infrastructures such as …
are required to ensure the serviceability and integrity of concrete infrastructures such as …