Multi task learning with incomplete labels for predictive maintenance
US11231703B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 14, 2019 |
| Grant date | Jan 25, 2022 |
| Priority date | — |
| Expiry date | Dec 26, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/048
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Example implementations described herein involve, for data having incomplete labeling to generate a plurality of predictive maintenance models, processing the data through a multi-task learning (MTL) architecture including generic layers and task specific layers for the plurality of predictive maintenance models configured to conduct tasks to determine outcomes for one or more components associated with the data, each task specific layer corresponding to one of the plurality of predictive maintenance models; the generic layers configured to provide, to the task specific layers, associated data to construct each of the plurality of predictive maintenance models; and executing the predictive maintenance models on subsequently recorded data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.