About this document
1 s2.0 S2352710225032681 Main by mamaku is a document available to read on EtoBox.
This paper presents a novel method for unsupervised structural damage localization that integrates a residual convolutional autoencoder (RCAE) with multi-feature Bayesian fusion, addressing challenges posed by environmental variability. The approach utilizes empirical wavelet transform for signal decomposition, enabling effective extraction of damage-sensitive features and robust damage localization through reconstruction residuals. Experimental results demonstrate the method
- Author
- mamaku
- Language
- EN