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:
Nov. 17, 2020

Filed:

Apr. 20, 2018
Applicant:

General Electric Company, Schenectady, NY (US);

Inventors:

Annarita Giani, Niskayuna, NY (US);

Masoud Abbaszadeh, Clifton Park, NY (US);

Lalit Keshav Mestha, Month Colonie, NY (US);

Assignee:

GENERAL ELECTRIC COMPANY, Schenectady, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 29/06 (2006.01); G06K 9/62 (2006.01); G06F 21/50 (2013.01); G06F 11/00 (2006.01); G05B 19/048 (2006.01);
U.S. Cl.
CPC ...
H04L 63/1425 (2013.01); G05B 19/048 (2013.01); G06F 11/006 (2013.01); G06F 21/50 (2013.01); G06K 9/6267 (2013.01); G06K 9/6297 (2013.01); H04L 63/14 (2013.01); G06F 2201/86 (2013.01);
Abstract

According to some embodiments, a plurality of monitoring nodes may each generate a series of current monitoring node values over time that represent a current operation of the industrial asset. A node classification computer may determine, for each monitoring node, a classification result indicating whether each monitoring node is in a normal or abnormal state. A disambiguation engine may receive the classification results from the node classification computer and associate a Hidden Markov Model ('HMM') with each monitoring node. For each node in an abnormal state, the disambiguation engine may execute the HMM associated with that monitoring node to determine a disambiguation result indicating if the abnormal state is a result of an attack or a fault and output a current status of each monitoring node based on the associated classification result and the disambiguation result.


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