Design And Application Of Aided Decision System For Salvage And Rescue At Sea

Recent years, many accidents, which bring lives away and caused significant loss of economic, had happened at sea. Responding to marine emergencies scientifically has become essential. After the incidents appear at sea, the most important thing is quickly and accurately locking the location of targets, or confines the waters at least. The drift of a hazardous target is a dynamic process. In order to lock its location, we always try to establish communications with it, which are decided by many factors, such as the target's situation, technology, etc.China's maritime search and rescue operations, mainly artificial carpet search, cannot make a large area or all-weather search. So, in China, rescue relies on the existing decision-making system is difficult to make a quickly search, confine the accurately location, or rescue at sea. And the result is we always miss the best time delay in search and rescue.The core problem that the theory of optimal search, is optimizing the search resources, whose distribution of the total search resources is limited and target is uncertainty distribution, to get the largest search in a minimum cost. Therefore, optimize the search of resources using the optimal search theory can greatly improve search quality.This paper has a systematic analysis of the status of maritime rescue search. And it expresses the factor of optimal search in target and search resources. It proposes an optimal search at emergencies at sea, and establishment of a decision support system of maritime search and rescue.First, we propose the aim and idea of this decision support system of maritime search and rescue. And design it combining the flow of maritime search and rescue in our search.Second, we have reached the drift of sea targets theory. According to the location of hazardous targets, we make sure the search area in a method of Monte Carlo, which is combining the information of Ocean currents and sea surface wind field. And we get the sub-divided the search area using the difference of target-distributions in different areas.Then, we assign the reach resources in sub-areas. We use the results of the optimal theory search, and see the target distribution function in sub-area as the detection function. Using optimal search method with limited search resources (effective search time), we finally get it. We have Case Studies using Decision support system in a random sea. The results of them prove the method proposed in the paper has a 16.62%, and has a 15.72% higher performance than search in the average time distribution method.Finally, we develop the Decision support system in Windows with Microsoft Visual Studio. NET 2003 combined with Electronic Chart Display and Information System (ECDIS) and the marine environment database.