Research On Identification And Positioning Of Thesis Tube Coils Based On RFID

Radio Frequency Identification(RFID)is a contactless system that automatically identifies and obtains target information through radio frequency signals for storing and transmitting data.The technology has been widely used in logistics,supply chain management,inventory management,transportation,safety management and other fields,and its advantages include automation,efficiency,real-time,contactless,multi-tag recognition,strong anti-interference,etc.However,its shortcomings cannot be ignored,including short communication distance,slow transmission rate,small tag storage capacity,and limited anti-interference ability.The research goal of this thesis is to realize the identification and positioning of thesis tube coils based on RFID technology.In order to achieve this goal,this thesis will study the identification and positioning technology of thesis tube coil based on RFID.The main work includes:(1)Aiming at the application of RFID technology in the identification and positioning of thesis tube coils,multiple factors will affect the accuracy of the identification and positioning effect,this thesis conducts experimental tests on the communication impact of elements such as coil diameter,test angle,tag mating method,tag type and signal strength on RFID passive tags.Through the experimental analysis of the multi-factor influence tag recognition effect,the feasibility of passive RFID technology in the application of thesis tube web identification and positioning direction is proved.(2)Aiming at the problem that the traditional RSSI path loss localization method is greatly affected by the indoor environment and has poor tolerance of noise interference,this thesis proposes a positioning method that combines the ensemble learning algorithm random forest and the fingerprint localization algorithm.In this thesis,81 feature fingerprint labels will be constructed by this positioning method,and the label features will be binary classified to construct an identification model.The results show that the fingerprint recognition accuracy of the model is higher than 98.4%.(3)Aiming at the problem of fingerprint coordinate space limitation,in order to meet the application needs of a wider range of scenarios,this thesis improves the positioning accuracy of RFID tags on thesis tube rolls by correcting the predicted coordinates by probability phase angle.This method is modified twice after the combination of random forest and fingerprint positioning algorithm,which reduces the positioning error of the coordinate position of the tag to be measured by 27.9%,and effectively improves the robustness of the identification and positioning system.The results show that the positioning method can meet the actual production needs,which is of great significance for improving the production efficiency and quality control of thesis tube coils.