The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 11, 2016

Filed:

Jun. 01, 2012
Applicants:

Siegmund Düll, München, DE;

Alexander Hentschel, München, DE;

Volkmar Sterzing, Neubiberg, DE;

Steffen Udluft, Eichenau, DE;

Inventors:

Siegmund Düll, München, DE;

Alexander Hentschel, München, DE;

Volkmar Sterzing, Neubiberg, DE;

Steffen Udluft, Eichenau, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 19/00 (2011.01); G06N 99/00 (2010.01); G05B 17/02 (2006.01); G05B 23/02 (2006.01); G05B 13/04 (2006.01); G06N 3/04 (2006.01);
U.S. Cl.
CPC ...
G06N 99/005 (2013.01); G05B 13/04 (2013.01); G05B 17/02 (2013.01); G05B 23/024 (2013.01); G06N 3/0481 (2013.01);
Abstract

A method for the computer-supported generation of a data-driven model of a technical system, in particular of a gas turbine or wind turbine, based on training data is disclosed. The data-driven model is preferably learned in regions of training data having a low data density. According to the invention, it is thus ensured that the data-driven model is generated for information-relevant regions of the training data. The data-driven model generated is used in a particularly preferred embodiment for calculating a suitable control and/or regulation model or monitoring model for the technical system. By determining optimization criteria, such as low pollutant emissions or low combustion dynamics of a gas turbine, the service life of the technical system in operation can be extended. The data model generated by the method according to the invention can furthermore be determined quickly and using low computing resources, since not all training data is used for learning the data-driven model.


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