Design And Implementation Of Networking And Gateway In Wireless Temperature Sensor Network

With the development of wireless sensor networks,the applications that make use of sensor nodes to detect environmental parameters receive widespread attention.Among all the parameters in substation environment,the temperature is one of the most critical indicator.Through transmitting temperature information via wireless sensor networks and gateways to monitoring station timely in order for temperature detection,we can accurately understand the operational status and fault information of an substation equipment,which provides an important basis for the safe and reliable operation of the power system as well as historical information for fault analysis.This thesis designs and implements a self-organized network and gateway based on the environment of the specific substation and comparison of different wireless sensor network protocols.In the research process of wireless sensor network,this thesis proposed an improved localization framework based on maximum likelihood for blind wireless sensor network node,which accelerates positioning process in the premise of ensuring positioning accuracy.Achievements of this work are as follows:1)Designing and implementing a multi-level networking to adapt high-voltage substation environment,including serial communication,Zig Bee communication protocol,SPI communication,TCP / IP protocol communications.2)Designing and implementing a multi-purpose gateway which communicates with aggregation node in wireless sensor network via serial port.The gateway adopts Extended Temperature Acquisition protocol as its main internal protocol,which is a customized protocol referring to 376.1 protocol.The gateway realizes login,heartbeat,active report of temperature,generation of historical data curve and other functions.3)Studying localization algorithm in depth and proposed an improved localization framework based on maximum likelihood.This localization framework consist of early estimation of blind node's position using improved weighted centroid algorithm and final localization through maximum likelihood algorithm.This algorithm improves the localization speed with high accuracy.