Field experiment on a PSC-I bridge for convolutional autoencoder-based damage detection

초록

In this study, a field experiment was performed for damage detection on a PSC-I bridge based on a convolutional autoencoder using the damage detection approach proposed in a previous study by the authors. The field experiment measured the acceleration and strain data of the PSC-I bridge while a single vehicle passed the bridge; subsequently, these data were used to train and test the convolutional autoencoder-based damage detection model. The results of the test showed that the convolutional autoencoder-based model could perform accurate and robust damage detection. Furthermore, these findings indicate that the convolutional autoencoder-based damage detection could also perform satisfactorily in practice. The results of this study can form the basis to facilitate the adoption of the convolutional autoencoder-based damage detection method to monitor bridges in practice.

키워드