Transformer failure diagnosis method and system based on integrated deep belief network
US12131247B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 18, 2020 |
| Grant date | Oct 29, 2024 |
| Priority date | — |
| Expiry date | Aug 30, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A transformer failure diagnosis method and system based on an integrated deep belief network are provided. The disclosure relates to the fields of electronic circuit engineering and computer vision. The method includes the following: obtaining a plurality of vibration signals of transformers of various types exhibiting different failure types, retrieving a feature of each of the vibration signals, and establishing training data through the retrieved features; training a plurality of deep belief networks exhibiting different learning rates through the training data and obtaining a failure diagnosis correct rate of each of the deep belief networks; and keeping target deep belief networks corresponding to the failure diagnosis correct rates that satisfy requirements, building an integrated deep belief network through each of the target deep belief networks, and performing a failure diagnosis on the transformers through the integrated deep belief network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.