Specialists from Novosibirsk State Technical University (NSTU) have presented a new system for monitoring potentially dangerous defects in power transformers. It is based on mathematical models.
We have developed models that, based on the analysis of statistical data, allow us to quickly assess the technical condition of the transformer when taking oil samples. This will help determine the type and nature of the malfunction, identify the causes of its occurrence, and assess the degree of risk for further operation of the equipment.
Currently, to identify possible defects, operators analyze transformer oil with a certain frequency. The methodology of NSTU specialists allows making predictions based on one oil sample.
The system developers plan to refine the remote monitoring function. The approach proposed by NSTU specialists can be used for remote monitoring of a group of transformers of the same voltage class operating at substations of the distribution electrical network. In the future, this will allow engineers to increase the reliability of transformer equipment through monitoring and distributed control based on industrial Internet of Things technologies.
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