Transferring failure samples using conditional models for machine condition monitoring
First Claim
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.
3 Assignments
0 Petitions
Accused Products
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.
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Citations
18 Claims
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1. A computer-implemented method for predicting failure modes in a machine, the method implemented by the computer comprising:
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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. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A computer-implemented method for predicting failure modes in a machine, the method implemented by the computer comprising:
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receiving sensor data samples for each of a source machine and a target machine, and partitioning sensor data samples for each machine into data from one or more independent sensors, and data from one or more dependent sensors whose sensor values depend on data values of 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 a multivariate Gaussian distribution for the source machine and a multivariate Gaussian distribution for 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 a conditional Gaussian distribution for the source machine and a conditional Gaussian distribution for 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.
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11. A non-transitory program storage device readable by a computer, tangibly embodying a program of instructions executed by the computer to perform the method steps for predicting failure modes in a machine, the method comprising:
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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. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18)
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Specification