The Design And Implementation Of UAV Patrol Management Information System For Transmission Lines

With the rapid development of society and economy in our country,the scale of the power grid is gradually expanding and the number of users is increasing rapidly.Therefore,the traditional power grid management method can not adapt to the current social situation.In order to ensure the safe and stable operation of the power grid system,this thesis mainly studies the transmission line patrol management information system based on the unmanned aerial vehicle(UAV),which realizes intelligent analysis and abnormal labeling of patrol pictures and videos,improves the efficiency of transmission line patrol,and reduces the labor cost and patrol cycle.This thesis firstly expounds the research significance of transmission line patrol inspection,analyzes its current situation at home and abroad,and briefly explains the relevant technologies.Secondly,it analyzes,designs and implements the UAV patrol management information system of power transmission line in turn by adopting the ideas and methods of software engineering.On the basis of actual investigation and interview,the requirements analysis of the system was improved,the module function analysis was carried out,and then the system architecture was designed from the logical layer,including the overall architecture of the system,database design,etc.,and the overall framework of the system was established.Finally,on this basis,the functions proposed in this thesis are implemented by Python programming language,and the system is tested in terms of functionality,reliability and compatibility after implementation.The main functional modules of the system are system management,video and image processing,UAV data acquisition and statistical reports.The system management function discusses and realizes the specific permissions and operations of various users,ensuring the stable and safe operation of the system.The video and image processing function realizes video anomaly labeling and adopts image recognition technology to identify defects.The UAV data acquisition function designs and realizes the route planning and patrol management of the UAV,which ensures that the UAV can acquire the transmission line information and working status in real time during the patrol.The system uses the SIFT algorithm to describe the extracted video feature points,and then uses similar feature points for video splicing to expand the video shooting range,whichis more conducive to the analysis of transmission line anomalies.At the same time,with the increase of returned videos and labeled information,the system can use deep learning technology to train a more accurate model and improve the intelligence of the system.Finally,the main work of this thesis is reviewed,the shortcomings of this thesis are analyzed,and the future research direction is clearly pointed out,which lays a solid foundation for the follow-up research.