Siemens Corporate Research, Inc.

Christian Darken

Markus Loecher

Nugroho Iwan Santoso

Jochen Erdmann

A method for providing a virtual age estimation for predicting the remaining lifetime of a device of a given type, comprises the steps of monitoring a predetermined number of significant parameters of respective ones of a training set of devices of the given type, the parameters contributing respective wear increments, determining coefficients of a multivariate Hermite polynomial for modeling the wear increments determined from the training set operated to failure and whereof the respective virtual ages are normalized substantially to a desired norm value, deriving from the multivariate Hermite polynomial a formula for virtual age of a device of the given type, and applying the formula to the significant parameters from a further device of the given type for deriving wear increments for the further device.

Method and apparatus for providing a polynomial based virtual age estimation for remaining lifetime prediction of a system

A method for providing a virtual age estimation for predicting the remaining lifetime of a device of a given type, comprises the steps of monitoring a predetermined number of significant parameters of respective ones of a training set of devices of the given type, the parameters contributing respective wear increments, determining coefficients of a radial basis function neural network for modeling the wear increments determined from the training set operated to failure and whereof the respective virtual ages are normalized substantially to a desired norm value, deriving from the radial basis function neural network a formula for virtual age of a device of the given type, and applying the formula to the significant parameters from a further device of the given type for deriving wear increments for the further device.

Method and apparatus for providing a virtual age estimation for remaining lifetime prediction of a system using neural networks

A system for generating a diagnosis of the probable cause of detected faults. Preferably, a user interface is provided and a Bayesien network is employed wherein probabilities are generated automatically and a manual process is used to construct a probability table. The system also allows multiple hypotheses and/or diagnoses to be presented simultaneously to the operator.

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Carmel Valley, CA, United States of America

Christian Darken