Heat exchanger fouling determination using thermography combined with machine learning methods
US11480517B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 8, 2019 |
| Grant date | Oct 25, 2022 |
| Priority date | — |
| Expiry date | Jul 23, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01J5/48
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
Disclosed is a methodology for determination and prediction of heat exchanger fouling, such as polymer fouling in the circulation loop that forms part of the heat exchanger system. The buildup of a polymer or other undesired material deposit in the heat exchanger provides a distinctive temperature signature (thermal gradient) on the surface of the heat exchanger asset, which is visualized using a thermographic camera. Coupling images (thermograms) from the camera with a machine learning algorithm identifies fouling and, with knowledge of the historical data of the asset and operating and ambient conditions, enables prediction of future fouling. The thermal images provide several types, or orders, of temperature information that are indicative of locations vulnerable to fouling. In one case, the method uses machine learning applied to time-based temperature change/gradient information to detect hidden polymer fouling in areas that form part of the heat exchanger asset.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.