Method and system for analyzing gas leak based on machine learning
US10031040B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 28, 2017 |
| Grant date | Jul 24, 2018 |
| Priority date | — |
| Expiry date | Mar 28, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20081
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
Embodiments of the present invention provide a system for estimating a location of a gas leak, based on machine learning from forward gas concentration data provided by an analog or scale model including a gas source. The system improves significantly over previous systems by providing high quality, physically accurate forward modeling data inexpensively. During operation, the system configures an aerosol source at a first location to emit a gaseous aerosol. The system then configures a laser source to illuminate the aerosol with a laser sheet. The system may then obtain an image of a reflection of the laser sheet from the aerosol. The system may then analyze the image to quantify a three-dimensional concentration distribution of the aerosol. The system may then estimate, based on solving an inverse problem and an observed second gas concentration, a second location of a second gas source.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.