Research On Buoy Drift Warning And Cloud Management Platform

The buoy provides various navigation services for ships sailing and plays an extremely important role in the shipping industry.The traditional buoy management relies on shift inspections around the scene by boat,which is inefficient and uneconomical.The aims of maintenance are not clear,which cannot guarantee timely detection of various failures of the buoy and poses potential hazards to nearby ships.The different navigation authority were isolated from each other and applied in isolation,which restricts the improvement of the overall efficiency.Aiming at the problems in the buoys' management and maintenance mode,combining with the complex working enviroment of buoy,based on extensive reading of literature,and deepen understanding of the telemetry and telecontrol technology,the design and implementation plan of the buoys' cloud management platform are proposed finally.The buoys' terminal and cloud management platform adopt modular design.Using STM32 single chip microcomputer as the main control chip of hardware to schedule and control all modules.A dedicated communication protocol is designed to achieve GPRS data interaction between the terminal and the sever,and buoy position is obtained by GPS satellite module.In sight of the fact that scattered buoys' datum of navigation authorities at all levels are difficult to meet the demands of navigational informatization management.A management software design scheme based on the SSM(SpringMVC+Spring+MyBatis)framework is proposed in combination with the cloud server technology.In the end,the software is deployed in the cloud as a service to achieve one-stop management of multi-sector buoys.In addition,through investigations provided by several navigation authorities as Fuzhou and Yichang,it was found that the navigation aids systems sent false location drift warning frequently because of the imperfect buoys' drift algorithm.To solve this problem,combined with the GPS positioning principle,a navigation aid drift model was established,and a combined optimization method based on Kalman filter and ISODATA(Iterative Self Organizing Data Analysis)algorithm was proposed.This method improves the accuracy of the position drift calculation by clustering the filtered GPS data.It can not only reduce the maintenance cost,but also effectively reduce the false alarm of location drift.