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Title: Multi-class decision system for categorizing industrial asset attack and fault types

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 classifier computer, coupled to the plurality of monitoring nodes, may receive the series of current monitoring node values and generate a set of current feature vectors. The node classifier computer may also access at least one multi-class classifier model having at least one decision boundary. The at least one multi-class classifier model may be executed and the system may transmit a classification result based on the set of current feature vectors and the at least one decision boundary. The classification result may indicate, for example, whether a monitoring node status is normal, attacked, or faulty.

Inventors:
; ;
Issue Date:
Research Org.:
General Electric Co., Schenectady, NY (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1651038
Patent Number(s):
10686806
Application Number:
15/681,827
Assignee:
General Electric Company (Schenectady, NY)
Patent Classifications (CPCs):
Y - NEW / CROSS SECTIONAL TECHNOLOGIES Y04 - INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS Y04S - SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
H - ELECTRICITY H04 - ELECTRIC COMMUNICATION TECHNIQUE H04L - TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
DOE Contract Number:  
OE0000833
Resource Type:
Patent
Resource Relation:
Patent File Date: 08/21/2017
Country of Publication:
United States
Language:
English

Citation Formats

Abbaszadeh, Masoud, Mestha, Lalit Keshav, and Yan, Weizhong. Multi-class decision system for categorizing industrial asset attack and fault types. United States: N. p., 2020. Web.
Abbaszadeh, Masoud, Mestha, Lalit Keshav, & Yan, Weizhong. Multi-class decision system for categorizing industrial asset attack and fault types. United States.
Abbaszadeh, Masoud, Mestha, Lalit Keshav, and Yan, Weizhong. Tue . "Multi-class decision system for categorizing industrial asset attack and fault types". United States. https://www.osti.gov/servlets/purl/1651038.
@article{osti_1651038,
title = {Multi-class decision system for categorizing industrial asset attack and fault types},
author = {Abbaszadeh, Masoud and Mestha, Lalit Keshav and Yan, Weizhong},
abstractNote = {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 classifier computer, coupled to the plurality of monitoring nodes, may receive the series of current monitoring node values and generate a set of current feature vectors. The node classifier computer may also access at least one multi-class classifier model having at least one decision boundary. The at least one multi-class classifier model may be executed and the system may transmit a classification result based on the set of current feature vectors and the at least one decision boundary. The classification result may indicate, for example, whether a monitoring node status is normal, attacked, or faulty.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {6}
}

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