Neural network based refrigerant charge detection algorithm for vapor compression systems
US7680751B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 31, 2006 |
| Grant date | Mar 16, 2010 |
| Priority date | — |
| Expiry date | Jan 2, 2029 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02T50/50
- WIPO fieldTransport
- WIPO sectorMechanical engineering
Abstract
Methods and apparatus are provided for determining refrigerant charge in a vapor compressor system (VCS) of an aircraft. The methods and apparatus comprise the following steps of, and/or means for, generating a data set from historical data representative of a plurality of VCS operating conditions over time, identifying one or more steady-state data points in the generated data set, forming a revised data set that includes at least the steady-state data points, using principal components analysis (PCA) to derive values for a plurality of minimally correlated input variables, supplying the derived values for the plurality of minimally correlated input variables and the corresponding values for the VCS refrigerant charge in the revised data set to a nonlinear neural network model, and deriving a simulator model characterizing a relationship between the plurality of minimally correlated input variables and the VCS refrigerant charge.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.