Method and system for predicting gas content in transformer oil based on joint model
US11914936B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 28, 2021 |
| Grant date | Feb 27, 2024 |
| Priority date | — |
| Expiry date | Feb 15, 2041 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH01F27/12
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and a system for predicting a gas content in transformer oil based on a joint model are provided and belong a field of transformer failure prediction. The method includes the following: determining a type and a time series of gas to be predicted related to a failure, processing an original series by adopting empirical mode decomposition (EMD) and local mean decomposition (LMD) for a non-stationarity characteristic of a dissolved gas concentration series in oil; performing normalization on each sub-series component, dividing a training sample and a test sample; and establishing a deep belief network (DBN) prediction model for each of the sub-series components for training, performing superposition and reconstruction on the established DBN prediction model to perform characteristic extraction and classification on multi-dimensional data of the failure, evaluating prediction performance of the prediction model through calculating an error index.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.