A two-step approach for damage identification in bridge structure using convolutional Long Short-Term Memory with augmented time-series data
This paper presents a novel two-step approach to identifying structural damages in bridge
structure through the integration of 1D Convolutional Neural Network (1DCNN) and Long …
structure through the integration of 1D Convolutional Neural Network (1DCNN) and Long …
[HTML][HTML] Data augmentation of dynamic responses for structural health monitoring using denoising diffusion probabilistic models
In the field of structural health monitoring, deep learning techniques are gaining increasing
recognition, with the fundamental requirement of high-quality data for effective …
recognition, with the fundamental requirement of high-quality data for effective …
Transferring self-supervised pre-trained models for SHM data anomaly detection with scarce labeled data
Structural health monitoring (SHM) has experienced significant advancements in recent
decades, accumulating massive monitoring data. Data anomalies inevitably exist in …
decades, accumulating massive monitoring data. Data anomalies inevitably exist in …