Oil-immersed transformer fault deduction visualization system based on big data association mining

Abstract

The invention discloses an oil-immersed transformer fault deduction visualization system based on big data association mining. The oil-immersed transformer fault deduction visualization system based on big data association mining performs fault hidden danger-fault symptom bidirectional deduction and association rule mining retrieval on typical state quantity fault types and fault symptoms of powertransformer working conditions through a big data analysis mining technology, and an efficient and intelligent power transformer fault diagnosis model and a case data retrieval management system areestablished, and the oil-immersed transformer fault deduction visualization system based on big data association mining is realized by using a virtual reality technology. In order to perform on-site rapid fault / hidden danger association deduction for operators by comprehensively utilizing historical operation and maintenance information, the operation and maintenance operators are assisted in performing rapid and reliable analysis and decision on the operation state of the power transformer, and finally the intelligence and reliability level of state maintenance of the power transformer is improved.

Description

technical field [0001] The invention relates to the technical field of power transformers, in particular to an oil-immersed transformer fault deduction visualization system based on big data association mining. Background technique [0002] The power transformer is an important pivotal equipment of the power system and an important part of the reliable coordinated operation of the source-network-load. The failure of the power transformer may lead to serious power system blackouts. However, various failures are common during its operation. For a long time, power companies still adopt the maintenance strategy of "regular maintenance mainly, supplemented by state-of-the-art maintenance" for transformers. As the demand for power grid economy and safety is getting higher and higher, it is an inevitable trend for the development of equipment maintenance methods to implement on-line maintenance of power transformers. Therefore, it is necessary to improve the level of transformer op...

AI Technical Summary

Problems solved by technology

[0003] Power transformers have large transmission power and complex structures. Hidden dangers / defects in different parts will lead to power transformer failures, and different operating environments have great differences in the influence of power transformers on their working status.

Moreover, when a fault occurs, it often not only causes a change in the state of one fault symptom, but also causes simultaneous multi-fault type defects caused by multiple fault symptoms, which makes the complex cross-mapping correlation between fault symptoms and fault types, It is difficult to rely on the accumulation of expert experience and knowledge, and the versatility is poor. It is difficult to rely on the establishment of a power transformer expert system to solve the problem of transformer fault diagnosis and prediction, so that the operation and maintenance personnel have brought great difficulties to the effective state evaluation of power transformers.

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