Fine-tuning DSAE-based anomaly-locating model of underwater mooring system

Abstract

Aiming at the difficulty of anomaly locating of the underwater mooring system, this paper develops an anomaly-locating algorithm based on the Deep Stark Auto-encoder (DSAE) network. Specifically, based on the real design parameters of a semi-submersible platform, a hydrodynamic model was established. Damage degrees of 5%was selected based on the DNV standard. The analysis of the responses was carried out when the anchor chain was damaged in different positions. Then an anomaly-locating model was established based on the DSAE method. The locating accuracy reached 99.13%. In contrast, the complete states were recognised as the damaged state. Furthermore, the established model was retrained by the fine-tuning operation. The locating accuracy reached 100% which can guide the safe service of the platform.