Research Of The Factory Sewage Wireless Monitoring System Based On Data Fusion

Water is the source of life and has an important role to human survival and development.With the development of industry and the increasing of wastewater sewage,the situation of water pollutions is more and more grim.Water environment monitoring and water quality evaluation are playing an important role in water environment protection and management.The paper analyzes current status of water quality environment monitoring system study around the world.According to the characteristics of water sewage monitoring system,being combined with wireless sensor network,data fusion algorithm is used in the factory sewage monitoring system The paper proposed that research of the factory sewage wireless monitoring system based on data fusion.The main contents are as follows.(1)Current status of research and technology on Water Environment Monitoring System at home and aboard are described Research of wireless sensor network and data fusion algorithm,the wireless sensor network combined with data fusion is applied to the factory sewage monitoring system.(2)The paper takes a certain ammonia nitrogen factory in huai'an as th research object and presents a multi-level data fusion algorithm based on temperature,PH,ammonia nitrogen,dissolve oxygen,turbidity five sewage parameters,which are used to evaluate the grade of sewage.The paper uses structure of distributed detection.Data fusion is composed of data-level fusion,feature-level fusion and decision-level fusion.Data-level fusion uses the grubbs criterion and the median average method for a signal sensor many times measurement results to eliminate distortion data and improve the accuracy of measurement;Feature-level fusion is based on the data of monitoring-area measured by the common sensors which is adaptive-weighted-algorithm;Decision-level data fusion is based on five components in the region,which derives level of the factory sewage,which is GA-BP neural network.(3)The system hardware circuit is designed It includes that the detection node,gateway and the monitoring center.Each part adopts the idea of modularity.The detection node includes the sensor module and the network communication module.The sensor module is responsible for collecting the data of each parameter,and CC2530 is adopted for data fusion and wireless communication in network communication module.The design of gateway hardware is CC2530+STM32+GPRS.CC2530 are responsible for networking and communication.STM32 is responsible for data fusion.GPRS is responsible for remote transfer data.Monitoring center uses the computer to operate.(4)Software design.The software of the system is designed.In the detection node:firstly,using the Grubbs criterion eliminates the doubtful data,and then the median average method is used to improve the reliability and accuracy of data;.In the gateway,the paper uses the adaptive weighting algorithm to obtain an optimal value for multiple sensors.In the monitoring center,the paper uses the GA-BP neural network for data fusion.First,the gentic algorithm is used to optimize the BP neural network,and then the trained GA-BP neural network is used to evaluate the water quality and get a whole index.The paper uses the LabView to write the friendly interface of the upper monitor and release in web.(5)Finally,we test the whole water monitoring system and assess the performance of the system.The results show that the system has a stable communication capacity and can accurately evaluate the grade of factory sewage.Moreover,the system possesses high reliability,high universality,high accuracy,etc.So it has a good application prospect...