Research On Video Monitoring Technology Of Growth Beneath The Transmission Lines

A identification and localization method based on binocular vision and image processing technology for the growth beneath transmission lines is presented in this paper, aiming to realize video monitoring and recognition of the growth beneath transmission lines. According to the characteristics of transmission lines video image, the method fits boundary conductor of transmission lines making use of spacers’position information and locates offline security range, and then realize the growth monitoring and localization within safety area.In order to calibrate cameras of transmission line, parameter estimation algorithm based on Zhang plane calibration method is applied. This algorithm calculates the parameter of rotated camera without calibration. A fast template matching algorithm based on the direction field optimization, which adopts gradient direction field technology to locate transmission line area firstly, and combines normalized correlation matching algorithm and histogram matching algorithm to locate spacers in images. In the process of calculation security range model, algorithm gets3D information of multiple spacers in the same line by binocular vision technology firstly, and then fits transmission line according Catenary Theory. At last, algorithm calculates safety area mathematical model based on the fitting results and transmission line safety area. In the process of growth identification and location, algorithm determines the offline security area model of image and detects the quasi growth point within it. And last, algorithm relocates the point to determine whether it match space security area model, and then determine whether there is dangerous. It will be dangerous if quasi growth point match the model, and thus, algorithm realizes real-time monitoring and location of offline growth.Experimental results show that algorithms can fit the lowest position of transmission line so as to realize accurate positioning of dangerous growth within safe area. In addition, it can also provide reference information for the extraction of transmission line sag. The algorithm of good real-time performance, high accuracy, improve the monitoring function of remote video monitoring system and provides technical support for the safety and reliability of power system.