Neural network feature recognition system
US10504220B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 25, 2017 |
| Grant date | Dec 10, 2019 |
| Priority date | — |
| Expiry date | Jun 7, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30164
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system includes one or more processors configured to analyze obtained image data representing a rotor blade to detect a candidate feature on the rotor blade and determine changes in the size or position of the candidate feature over time. The one or more processors are configured to identify the candidate feature on the rotor blade as a defect feature responsive to the changes in the candidate feature being the same or similar to a predicted progression of the defect feature over time. The predicted progression of the defect feature is determined according to an action-guidance function generated by an artificial neural network via a machine learning algorithm. Responsive to identifying the candidate feature on the rotor blade as the defect feature, the one or more processors are configured to automatically schedule maintenance for the rotor blade, alert an operator, or stop movement of the rotor blade.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.