Research on Real-Time Early Warning Method for Scrapping Failure Risk of Large Power Grid Equipment

At present, the real-time early warning nodes of equipment scrap failure risk are mostly independent structures, and the scope of early warning is limited, which leads to the increase of early warning variance. Therefore, the design and verification of real-time early warning method for scrap failure risk of large-scale equipment in power grid are proposed. According to the current test requirements and standards, the basic early warning targets of power grid equipment scrapping failure are extracted first, and the multi-objective method is adopted to break the limitation of early warning range, and multi-objective risk real-time early warning nodes are deployed. On this basis, a real-time early warning model of power grid equipment scrapping failure risk based on big data mining is constructed, and real-time early warning processing is realized by tracking and positioning. The test results show that: for the selected five test cycles, the test and early warning of power equipment are carried out in three stages, and the final early warning variance is well controlled below 1.5, which shows that the real-time early warning effect of scrap failure risk of the current design is better, more targeted and has practical application value.