Wang, Y. and Li, Y.-R., 2020. Fault diagnosis of underwater vehicle propulsion system based on deep learning. In: Qiu, Y.; Zhu, H., and Fang, X. (eds.), Current Advancements in Marine and Coastal Research for Technological and Sociological Applications. Journal of Coastal Research, Special Issue No. 107, pp. 65-68. Coconut Creek (Florida), ISSN 0749-0208.
The 21st century is the marine era. Marine economy has played an important role in promoting global economic development, which requires us to continuously develop marine resources. The underwater vehicle is an important tool for human to understand the ocean and explore the marine resources, which has a good application prospect in the exploration of marine environment, resource development and military applications. With the development of ocean strategy, the safety and stability of underwater robot becomes the most important problem, which requires us to improve the performance of the work. Propulsion system is the core of the underwater robot, which requires us to do a good job in motion control and fault diagnosis. However, in the complex marine environment, the underwater robot will be affected by many aspects, which will cause the diversity of propulsion system fault. How to effectively identify and diagnose fault types has become the most important problem, which will help us to improve the motion control performance and survivability of underwater robots.