Research On Early Warning System Of Transmission Line Protection Against External Force Damage Based On Machine Vision

Transmission lines bear the important task of power transmission in the power system,and ensuring its safe operation is an inevitable requirement for building a strong smart grid.External force damage is an important cause of overhead transmission line faults.The existing technology of power line inspection has obvious hysteresis defects in finding failure caused by external force,while the traditional on-line monitoring technology has a high false alarm rate due to the lack of accurate target recognition ability,which has made it increasingly difficult for these technologies to adapt to the rapid development of the power grid.With the development of machine vision technology,intelligent devices have been applied in various fields.This paper mainly studies the forewarning system of transmission lines against external force damage using intelligent video surveillance technology.The system realizes the function of intelligent alarm through motion detection and target recognition,which solves the problem of high false alarm rate of traditional on-line monitoring methods.Firstly,this thesis introduces the basic motion detection methods.Based on the analysis of video surveillance scenes of overhead transmission lines,an improved Gaussian Mixture Modeling method using region of interest and three-frame difference method is proposed.By calibrating the region of interest,the motion detection sensitive region,the motion detection non-sensitive region and the shielding region are divided,which improves the efficiency of the algorithm and achieves the goal of key monitoring in key areas.The learning rate is dynamically adjusted according to the relative change amount of the frame detected by the three-frame difference method,so that the Gaussian Mixture Model can adapt to various conditions.The final moving target is obtained by morphological fusion and noise reduction of the two differential images obtained by the three-frame difference method and the Gaussian Mixture Modeling method.This improved algorithm has the ability to detect moving targets quickly and accurately,and exhibits good detection results in the external force damage forewarning system.Secondly,aiming at crane collision,which is the main cause of the external force damage,a target recognition algorithm based on feature fusion and random forest is proposed.In order to improve the accuracy of recognition of specific targets,the extraction method of "shape-texture-color" is designed based on the analysis of the characteristics of cranes: the improved edge line detection method is used to extract the shape features of crane boom;obtaining the texture information by using the LBP operator in uniform pattern;obtaining the color features of the target in the HSV color space quantified by two-step method.The three features collected are cascaded into fusion features and then applied in target recognition based on random forest classifier.If the target is identified as a crane,a danger level will be generated according to the posture and distance of the crane,so as to provide information for follow-up early warning of crane collision.Experiment results show that the recognition accuracy of this algorithm on the crane image library is 90.6% in average,which means it can be applied to intelligent video surveillance system of the transmission lines.Finally,this thesis constructs an early warning system for the prevention of external force damage of transmission lines,which consists of front-end monitoring system and back-end service system.The front-end monitoring system carries out video acquisition,processing and local alarm work;while the back-end service system displays the information to the monitors through the upper software;data backhaul and remote control are implemented by wireless communication between the front-end and the back-end.The experimental results show that the front-end device can work stably under a wide range of load currents,and realize the intelligent video monitoring and alarm function at the same time;the monitor can easily configure and control the front-end device through the upper software,and intuitively obtain the failure information caused by the external force of the transmission line.The forewarning system of transmission lines against external force damage based on the researches of this thesis works well,and can play an active role in the development of intelligent monitoring technology of transmission lines.