The Algorithm Of Intelligent Video Monitoring On Electrical Equipment Temperature And Partial Discharge

With smart power grids presented and the development of the power systemautomation technology， especially our country has already promoted theunattended substation operation mode. Our traditional power system automationsystem only realizing "four remote" function, now we need configure a completeset of video surveillance system for substation on the basis of "four remote"function, and realize the fifth remote function" remote viewing"。The mainly ismonitoring on electrical equipment operational status. It can ensure safeoperation of electrical equipment, and plays important role in improving thereliability of power system.Because of our country electric power system conditions, leading to thecurrent electrical equipment monitoring method has certain insufficiency: thefirst, the present methods are inspection methods, so it can’t satisfy the powersystem intelligent demand; second, the methods are generally lagging, not earlywarning; third, the detection methods are in their respective cases arerespectively monitor without catholicity, causing a lot of material waste.It’s the first time that this paper applies intelligent video technology onelectrical equipment operating temperature and partial discharge onlinemonitoring. Filter the collected electric equipment operation in real time videoimage, then intelligently identify the electrical equipment temperature anomaliesand partial discharge condition by dynamic three frame detection and backgrounddifference method. To intelligently analysis the detected the abnormal videoimage and preliminary diagnose electrical equipment fault types and perhapscauses of fault. Application of relative temperature difference method intelligently judges the electrical equipment fault type, then through thetemperature rise characteristics of preliminary diagnoses the possible reasons forabnormal. Application of Canny edge detection method deals with each frame ofthe video image to eliminate the influence of background light. Then the systemdetects the results of edge detection image frame by frame with frame differencemethod, what’s more, intelligently identify discharge area. According to thedischarge area and brightness, it intelligently analyses of partial discharge andinsulation damage degree. This paper uses OpenCV software platform to realizethe whole system design and realization of intelligent recognition function. Whenthe system detects the abnormal video image, the central control send videoimages and judging result through wireless network is sent to the mobile phoneof staff. The staff can obtain the scene information on time and deal with faulttimely.Through the application of intelligent video technology for remote on-lineintelligent monitoring to power system operation status of the electricalequipment can make up the defects of current methods and meet the requirementsof the development of intelligent power system. The method achieves the“remote viewing" function of power system in the true sense, and intelligentlyensure the reliability of power system.