Font Size: a A A

Research On The Sea Rescue Of Large Amphibious Aircraft

Posted on:2019-11-02Degree:MasterType:Thesis
Country:ChinaCandidate:Z WuFull Text:PDF
GTID:2382330596450429Subject:Engineering
Abstract/Summary:PDF Full Text Request
Aviation rescue is a new branch of aviation research in recent years.AG-600 is a new generation of rescue aircraft of our country.Aiming at the new equipment and new problems,it is necessary to research it.In different search circumstances,the same success rate of rescue obviously represents different search and rescue effects.Aiming at improving existing maritime search and rescue effect,evaluation is not objective enough.The maritime search and rescue ability evaluation method proposed in this paper is not just for large amphibious aircraft,but also can be used as a maritime search and rescue effect evaluation of objective reference.Accurately evaluating the rescue ability,therefore,can be targeted to moderate configuration rescue efforts,conducive to the smooth completion of the search and rescue work,avoid the rescue configuration and search rescue forces idle waste,in accordance with the need of sustainable development in China.Marine rescues is a very important part of amphibious rescue process.It means many aircraft sorties for the purpose of rapid relief,planning the whole rescue route.Putting in rescue boat to make it in accordance with a predetermined rescue route to save targets on the sea.Simulation of the process can give the rescue team timely feedback,and enhance the rescue efficiency.This paper introduces the significance of sea rescue and the principle and improving of ant colony algorithm and K-Means method in path planning.At the same time,in this paper I expound the development and the use of rescue software.The sea rescue software has a certain reference value on search and rescue and other path optimization problem in amphibious aircraft.
Keywords/Search Tags:rescue capability assessment, evaluation software, rescue on the sea, K-means clustering algorithm, ant colony algorithm
PDF Full Text Request
Related items