A novel approach model design for signal data using 1DCNN combing with LSTM and ResNet for damaged detection problem
In the current era, time-series data is widely used in different domains. In Structural Health
Monitoring (SHM), the utilization of time-series data is also extensive. However, traditional …
Monitoring (SHM), the utilization of time-series data is also extensive. However, traditional …
[HTML][HTML] Deep neural network and evolved optimization algorithm for damage assessment in a truss bridge
In Structural Health Monitoring (SHM) of bridges, accurately assessing damage is critical to
maintaining the safety and integrity of a structure. One of the primary challenges in damage …
maintaining the safety and integrity of a structure. One of the primary challenges in damage …
Enhancing time series data classification for structural damage detection through out-of-distribution representation learning
The analysis and classification of time series data, notably within Structural Health
Monitoring (SHM) systems, face profound challenges due to the nonstationary nature of the …
Monitoring (SHM) systems, face profound challenges due to the nonstationary nature of the …
[HTML][HTML] Effective applications of 1-D finite difference modeling for temperature prediction of concrete structures
This paper introduces a 1-D finite difference model for analyzing the temperature distribution
throughout the hardening phase in concrete structures. The model accounts for the degree …
throughout the hardening phase in concrete structures. The model accounts for the degree …
Enhancing Salp Swarm Optimization with Orthogonal Diagonalization Transformation for Damage Detection in Truss Bridge
This paper proposes a novel approach for structural damage identification using the Salp
Swarm Algorithm (SSA) combined with Orthogonal Diagonalization (OD). SSA is an …
Swarm Algorithm (SSA) combined with Orthogonal Diagonalization (OD). SSA is an …
Time series data recovery in SHM of large-scale bridges: Leveraging GAN and Bi-LSTM networks
This paper proposes the utilization of a Bidirectional Long Short-Term Memory (Bi-LSTM)
network and a Generative Adversarial Network (GAN) model, to recover measured time …
network and a Generative Adversarial Network (GAN) model, to recover measured time …
A Prospective Technique for Damage Detection in Truss Structures Using the Fusion of DNN with AVOA
In recent decades, the integration of optimization methods and Machine Learning (ML)
models has garnered significant attention within the research community. In the pursuit of …
models has garnered significant attention within the research community. In the pursuit of …
Damage Detection in Structural Health Monitoring Using an Integrated ANNIRSA Approach
In the past decade, artificial neural networks (ANNs) have been widely employed to address
many problems. Despite their powerful problem-solving capabilities, ANNs are susceptible …
many problems. Despite their powerful problem-solving capabilities, ANNs are susceptible …
[HTML][HTML] Temperature evolution and activation energy sensitivity analysis for early-age concrete elements using a 3-D finite difference model
Concrete structures are prone to cracking due to non-uniform temperature distribution
caused by the heat released during cement hydration. Accurate prediction of temperature …
caused by the heat released during cement hydration. Accurate prediction of temperature …