Complex system anomaly detection based on discrete event sequences
US11520981B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 11, 2020 |
| Grant date | Dec 6, 2022 |
| Priority date | — |
| Expiry date | Jun 18, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/042
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method detects anomalies in a system having sensors for collecting multivariate sensor data including discrete event sequences. The method determines, using a NMT model, pairwise relationships among the sensors based on the data. The method forms sequences of characters into sentences on a per sensor basis, by treating each discrete variable in the sequences as a character in natural language. The method translates, using the NMT, the sentences of source sensors to sentences of target sensors to obtain a translation score that quantifies a pairwise relationship strength therebetween. The method aggregates the pairwise relationships into a multivariate relationship graph having nodes representing sensors and edges denoted by the translation score for a sensor pair connected thereto to represent the pairwise relationship strength therebetween. The method performs a corrective action to correct an anomaly responsive to a detection of the anomaly relating to the sensor pair.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.