Population-based learning with deep belief networks
US10733536B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 29, 2017 |
| Grant date | Aug 4, 2020 |
| Priority date | — |
| Expiry date | Aug 16, 2038 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02P90/02
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
A plant asset failure prediction system and associated method. The method includes receiving user input identifying a first target set of equipment including a first plurality of units of equipment. A set of time series waveforms from sensors associated with the first plurality of units of equipment are received, the time series waveforms including sensor data values. A processor is configured to process the time series waveforms to generate a plurality of derived inputs wherein the derived inputs and the sensor data values collectively comprise sensor data. The method further includes determining whether a first machine learning agent may be configured to discriminate between first normal baseline data for the first target set of equipment and first failure signature information for the first target set of equipment. The first normal baseline data of the first target set of equipment may be derived from a first portion of the sensor data associated with operation of the first plurality of units of equipment in a first normal mode and the first failure signature information may be derived from a second portion of the sensor data associated with operation of the first plurality of u…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.