Research And Design Of Remote Water Quality Ammonia Nitrogen Monitoring System

Ammonia nitrogen content is an important factor to evaluate water quality.Excessive ammonia content in water can affect the growth of aquatic organisms and cause water pollution.In the Yangtze river and qiantang river,the ammonia nitrogen content in the river basin has caused the pollution of cyanobacteria.It caused industrial water and drinking water in the surrounding area to be unusable.Therefore,the water quality environmental protection department began to increase the monitoring of ammonia nitrogen content.Although the traditional ammonia nitrogen monitoring system can realize remote real-time monitoring,it is not widely used in the field of water quality monitoring due to the high development cost and low intelligence level.For the above problems,based on shaanxi industrial science and technology research project 2016GY-044,the team members designed a set of remote water quality ammonia nitrogen monitoring system.The main work of this paper is to realize remote real-time monitoring and data management analysis of water quality ammonia nitrogen based on the existing on-site water quality ammonia nitrogen detection system in the laboratory.At the same time,in order to prevent ammonia nitrogen pollution,this paper proposes a feasible algorithm to predict ammonia nitrogen content.The system consists of two parts: site inspection station and remote monitoring center.The site inspection station completes data collection,display and upload.In the data transmission part,the system adopts VPN tunnel technology to guarantee the security of data transmission.Remote monitoring software development based on MFC framework and C/S network architecture.The software of this system is divided into data reliable transmission design,real-time monitoring design and data management analysis design.Based on BP neural network,the prediction model of water quality ammonia nitrogen was established,and the BP neural network ammonia nitrogen prediction model was optimized by genetic algorithm.The feasibility of the prediction algorithm is verified by Matlab simulation.Finally,with the help of the laboratory platform,the whole system is debugged,and the whole system can work smoothly.