Automatic sampling of seawater quality based on electric propulsion unmanned ship

Abstract

Abstract In many sea areas, toxic and harmful chemicals vastly exceed the standard, which not only has had a very bad impact on the survival of marine organisms, but also damages the safety of edible groundwater. With the continuous development of artificial intelligence and deep learning, the most efficient and safe method to detect seawater is with unmanned ship. By processing and fusing the images transmitted by the two radars, the common advantages of the two sensors are integrated, and the comprehensiveness of the unmanned aerial vehicle's (UAV;s) perception of the surrounding environment is improved. In order to improve the accuracy and safety of UAV offshore operations, this study designed an electric propulsion unmanned ship and its automatic control system according to the requirements of water quality sampling. Based on the small body theory, the model of an unmanned ship with the least resistance and the best safety is designed. According to the requirements of water quality sampling in sea areas, the vessel was equipped with collection and analysis systems to measure six elements of water quality. The Realizable k-e turbulence model was used to simulate the self-recovery ability of an unmanned ship under wave disturbance. Theoretically, the unmanned ship can achieve self-righting in 4.25 s. For actual navigation, the unmanned ship can effectively avoid obstacles, and the basic information on seawater quality was within the specified range. The unmanned ship constructed in this study can be used as an auxiliary tool for water quality detection. Compared with various study methods, the proposed method obtained a better performance.