Patent · US Active

Transferring failure samples using conditional models for machine condition monitoring

US10108513B2 · kind B2 · utility

1Cited by

5References

18Claims

0Family size

Assignee

Siemens Aktiengesellschaft · DE

Inventors

Chao Yuan · Plainsboro, US
Amit Chakraborty · Plainsboro, US
Holger Hackstein · Dietzenbach, DE
Hans-Werner Weber · Ingolstadt, DE

Key dates

Filing date	Apr 16, 2014
Grant date	Oct 23, 2018
Priority date	—
Expiry date	Oct 11, 2034

Classification

Technology area (CPC G)Physics
CPC primaryG06N20/10
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

A method for predicting failure modes in a machine includes learning (31) a multivariate Gaussian distribution for each of a source machine and a target machine from data samples from one or more independent sensors of the source machine and the target machine, learning (32) a multivariate Gaussian conditional distribution for each of the source machine and the target machine from data samples from one or more dependent sensors of the source machine and the target machine using the multivariate Gaussian distribution for the independent sensors, transforming (33) data samples for the independent sensors from the source machine to the target machine using the multivariate Gaussian distributions for the source machine and the target machine, and transforming (34) data samples for the dependent sensors from the source machine to the target machine using the transformed independent sensor data samples and the conditional Gaussian distributions for the source machine and the target machine.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.