Online monitoring method of nuclear power plant system based on isolation forest method and sliding window method
US12050449B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 10, 2022 |
| Grant date | Jul 30, 2024 |
| Priority date | — |
| Expiry date | Nov 29, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG05B2219/161
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
The present disclosure relates to an online monitoring method of a nuclear power plant system based on an isolation forest method and a sliding window method. An isolation forest method used in the present disclosure is an abnormal detection model based on the idea of binary tree division, and has no requirements on the dimension and linear characteristics of monitoring data. In view of the characteristics of strong nonlinearity and high dimension of operation data of the nuclear power plant system, in the process of state monitoring, system abnormalities can be detected more quickly and accurately. In the present disclosure, a sliding window method is used to improve an isolation forest model, so that the improved isolation forest model has the functions of model online updating and real-time state monitoring, and the usability of an isolation forest state monitoring method is enhanced.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.