Real time machine learning based predictive and preventive maintenance of vacuum pump
US11002269B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 22, 2019 |
| Grant date | May 11, 2021 |
| Priority date | — |
| Expiry date | Jan 22, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01M3/26
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
A method and system of a machine learning architecture for predictive and preventive maintenance of vacuum pumps. The method includes receiving one of a motor sensor data and a blower sensor data over a communications network. The motor sensor data is classified into one of a vacuum state sensor data and break state sensor data. The vacuum state sensor data is analyzed to detect an operating vacuum level and an alarm is raised when the vacuum state sensor data exceeds a pre-defined safety range. Vacuum break data is classified into one of a clean filter category and clogged filter category and an alarm is raised if an entry under the clogged filter category is detected. The blower sensor data in association with the motor sensor data is analyzed based on machine learning to detect one of a deficient oil level and a deficient oil structure.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.