Patent Document ID: 10108513
Application ID: 15303243
Patent Flag: 1

Claim One:
1. A computer-implemented method for predicting failure modes in a machine, the method implemented by the computer comprising: learning 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, wherein said data samples are acquired under normal operating conditions for each machine; learning 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 said source machine and said target machine using the multivariate Gaussian distribution for the independent sensors, wherein said data samples are acquired under normal operating conditions for each machine; transforming 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; transforming 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, acquiring data samples from the independent sensors of the source machine associated with a failure; transforming said failure 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 said failure 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.