Submarine pile foundation and cable monitoring based on sensor fusion and big data analysis

With the development of marine resources and offshore wind power, submarine piles and cables are facing safety challenges such as anchor damage and aging, this paper proposes an intelligent monitoring method based on multi-source sensor fusion and big data analysis. Through the integration of fibre optic sensing, MEMS array real-time collection of cable strain-temperature and pile displacement data, combined with the automatic identification system (AIS) and video surveillance to build a multi-dimensional sensing network, the use of distributed fusion algorithm to establish the strain-temperature correlation threshold and the introduction of deep learning optimisation of positioning. Verification in Hainan networking project and other scenarios show that: the efficiency of cable detection is improved by 40%, the accuracy of pile crack identification reaches 98%, and the three-dimensional positioning error is less than 0.5 metres, which effectively enhances the real-time monitoring of submarine facilities and active early warning capabilities.