Creating predictive damage models by transductive transfer learning
US10229369B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 19, 2016 |
| Grant date | Mar 12, 2019 |
| Priority date | — |
| Expiry date | May 23, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG05B23/0283
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for creating predictive damage models includes receiving a first predictive damage model, identifying latent space between a first and a second domain asset, building a regression model from first domain asset projected source data, creating target dependent variables of a second model, applying classification or regression techniques to determine a function expressing the dependent variables, determining data points from the function to develop a second regression model, applying the second regression model to data points to predict target dependent variables, evaluating the second predictive damage model using the predicted target dependent variables, performing a sensitivity study to determine a directionality parameter of the second predictive damage model, and if the results are within an acceptable predetermined range, providing maintenance or servicing recommendations generated by the second predictive model to a user platform display, else repeating the process by rebuilding the regression model to further refine the regression model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.