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With the arrival of the digital era, the substation has got rid of the previous operation mode and gradually turned to digitalization and modernization, which reduces the risk brought by manual operation and improves the efficiency and quality of substation operation. But substation in electric power equipment failure problems will not be able to avoid, need regular maintenance/repair, and internal defects for some electric power equipment, it is hard to recognize by the naked eye or experience, even if can preliminarily judge the failure problems, also can’t accurate positioning, need to use modern methods to solve. Based on this, this paper takes the sample of transformer oil tank as the research object, diagnoses the internal defects of the sample with the help of laser focusing enhancement technology, and obtains the imaging results of internal defects and specific defect parts. The verification results show that the imaging results and specific defect parts of the sample can be accurately obtained through this technology. The feasibility of the application of this technology in the fault diagnosis of substation power equipment is confirmed, and the fault can be detected in time to ensure the safety of the whole operation of the substation. [ABSTRACT FROM AUTHOR]

With the continuous improvement of science and technology, the substation patrol inspection has gradually stepped into the unmanned stage or the less humanized stage. Although the input of patrol robot improves the intelligence and modernization of substation patrol work, it also gives rise to some problems that are not favorable to the work of patrol robot, such as loose or bad contact of wired charging interface, copper oxidation at the electric end, etc., which restrict the normal work of substation patrol robot. Based on this, in order to avoid the occurrence of such problems, the core algorithm of electromagnetic resonance wireless charging technology is studied. To be specific, the existing wireless charging technologies are compared by comparison method, and magnetic resonance is finally chosen as the wireless power supply method in this paper, and then the design scheme of wireless charging device is given. Finally, the calculation method of coupling system efficiency and system output efficiency is given through the test of magnetically coupled resonant wireless charging efficiency. It is also pointed out that the radio energy transmission efficiency is affected by the coil distance, resonant frequency and the number of turns of the receiving coil. It can be seen that in practical engineering, we can focus on these factors to improve the efficiency of radio energy transmission and promote the work progress and efficiency of substation patrol robot. This research aims to promote the overall popularization of wireless charging technology for substation robots. [ABSTRACT FROM AUTHOR]

With the continuous improvement of science and technology, infrared image recognition technology has been popularized in the substation, and has become an important means of transformer equipment fault monitoring. At present, infrared image recognition technology can play a good recognition effect in open equipment fault detection, but it cannot directly get the recognition effect of closed equipment, so it needs to be processed by elimination method, which inhibits the application of image recognition technology in substation. Based on this, the infrared identification research is carried out with the 10kV trolley switch cabinet and GIS equipment as the research objects. To be specific, an on-line monitoring scheme for substation equipment fault based on image recognition is developed, and the scheme is applied in the infrared fault identification experiment of the trolley switch cabinet. The results show that the three-phase temperature of copper row behind the static contact seat of the trolley switch cabinet can be found through the perspective window, confirming the feasibility of the scheme. Then, the infrared fault identification experiment of GIS equipment was carried out to find the main cause of equipment heating, and the robustness of the scheme was confirmed again. Through this research, the importance of infrared image recognition technology in substation equipment fault monitoring is affirmed, and the problem that infrared image recognition technology can not directly obtain closed equipment state information is solved in the past, which improves the application of image recognition technology in substation equipment fault monitoring. [ABSTRACT FROM AUTHOR]