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:
Jul. 02, 2019

Filed:

Jun. 15, 2017
Applicant:

Siemens Aktiengesellschaft, München, DE;

Inventors:

Felix Borutta, Oberpframmern, DE;

Thomas Hubauer, Garching bei München, DE;

Peer Kröger, Oberpframmern, DE;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G08B 21/00 (2006.01); G08B 21/18 (2006.01); G07C 3/02 (2006.01); G06K 9/62 (2006.01); G05B 23/02 (2006.01); G06N 5/02 (2006.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G08B 21/187 (2013.01); G05B 23/0221 (2013.01); G05B 23/0254 (2013.01); G06K 9/6247 (2013.01); G06K 9/6272 (2013.01); G07C 3/02 (2013.01); G05B 2219/32201 (2013.01); G06N 5/02 (2013.01); G06N 20/00 (2019.01); Y02P 90/22 (2015.11);
Abstract

A sensor data stream is provided consisting of feature vectors acquired by sensors of rotating equipment, similar feature vectors are aggregated in microclusters. For newly arriving feature vectors, a correlation distance measure between the new feature vector and each microcluster is calculated. If there is no microcluster in range, then a new microcluster is created. Otherwise, the feature vector is assigned to the best fitting microcluster, and the necessary statistical information is incorporated into the aggregation contained in the microcluster. In other words, similar feature vectors are aggregated in the same microclusters. The microclusters thus provide a generic summary structure that captures the necessary statistical information of the incorporated feature vectors. At the same time, the loss of accuracy is quite small. Clustering the sensor data stream with microclusters has the benefit that the computational complexity can be reduced significantly.


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