Research On Multi-parameter Online Monitoring And Data Analysis Technology In Coastal Area

China has a long coastline.With the increasing shortage of land resources,the strategic position of marine resources development is increasingly important.However,while the ocean has brought us vast resources,it has also brought some threats.Natural disasters such as red tides,typhoons and storm surges have occurred from time to time,which has brought immeasurable losses to the country's property and has huge impact on people's life.Marine monitoring can provide multi-faceted,long-term,real-time data that is important for minimizing the damage caused by marine disasters.Among the many monitoring methods,near-coast cable monitoring can monitor ocean data for a long time and has an important position in ocean monitoring.In this thesis,based on the investigation of the status quo of offshore monitoring research at home and abroad,this thesis designs a set of near-coast multi-parameter online monitoring system to realize the continuous,real-time and automatic monitoring of offshore water quality parameters in line with the trend of marine monitoring automation and intelligence.Compared with the existing offshore monitoring system,the system has strong stability,more complete functions,and supports the later expansion of the sensor.The near-shore online monitoring system consists of a bottom-sense observation platform,a shore-based communication machine and a remote monitoring center.The bottom observation platform is responsible for monitoring sensor data and communication with the shore base.The shore based communication machine is responsible for data interaction between the bottom observation platform and the remote monitoring center and the energy supply to the bottom observation platform.The remote monitoring center is responsible for the presentation of data on the user side.Among them,the shore-based communication machine solves the problem of inconvenient on-site debugging by introducing the function of user interaction,and the remote monitoring center provides convenience for remote users to view data and data analysis.This thesis mainly studies the software and hardware design and implementation of the near-shore online monitoring system.The hardware part completes the hardware circuit design of the shore-based communication machine and the bottom observation platform with the industrial control board as the core,and makes the interface compatible with the common sensors on the market;the embedded software design part completes the customization and platform construction of WinCE,the design of the communication protocol,the application design based on multi-threading,etc.The program configures the system by reading the configuration file during initialization,which improves the versatility and expandability of the system.Besides,an exception handling mechanism for the abnormal situation that may occur in the system is designed in this thesis.The software design of the remote monitoring center is completed through Web technology,which can provide real-time data viewing,data review,early warning and other functions,and provide users with a friendly data presentation interface.Through system testing,it shows that the whole system can basically realize the design function.For the collected data,this thesis proposes an intelligent analysis method.Based on the in-depth study of the long-term memory neural network in deep learning,this thesis uses the particle swarm optimization algorithm to optimize the parameters and applies it to the analysis of red tide monitoring data,which achieves good results.