Systems and methods for remote monitoring, security, diagnostics, and prognostics

Patent metadata

Field	Value
Publication number	US-9245116-B2
Application number	US-201313848354-A
Country	US
Kind code	B2
Filing date	Mar 21, 2013
Priority date	Mar 21, 2013
Publication date	Jan 26, 2016
Grant date	Jan 26, 2016

Abstract

A system includes a physical analysis module, a cyber analysis module, and a determination module. The physical analysis module is configured to obtain physical diagnostic information, and to determine physical analysis information using the physical diagnostic information. The cyber analysis module is configured to obtain cyber security data of the functional system, and to determine cyber analysis information using the cyber security data. The determination module is configured to obtain the physical analysis information and the cyber analysis information, and to determine a state of the functional system using the physical analysis information and the cyber analysis information. The state determined corresponds to at least one of physical condition or cyber security threat. The determination module is also configured to identify if the state corresponds to one or more of a non-malicious condition or a malicious condition.

First claim

What is claimed is:

1. A system comprising:
a physical analysis module of hardware and software, the hardware including one or more sensors to detect a parameter corresponding to an operational or environmental state of a functional system to obtain physical diagnostic information describing at least one of the operational or environmental states of the functional system, and further determine physical analysis information using the physical diagnostic information;
a cyber analysis module of hardware and software comprising a communication link to a networking portion of the functional system to obtain cyber security data, and to determines cyber analysis information using the cyber security data;
a determination module of hardware and software that provides one or more models to identify a state of the functional system and an estimated life of the functional system, wherein the expected life is an expected secure life corresponding to a predicted time for which the functional system is expected to be secure from faults due to previous exposure to cyber attack, such that the determination module obtains the physical analysis information and the cyber analysis information, to determines a state of the functional system using the physical analysis information and the cyber analysis information, the state corresponding to at least one of physical condition or cyber security threat, and to identify if the state corresponds to one or more of a non-malicious condition or a malicious condition; and
a non-transitory computer readable storage medium including memory;
wherein the cyber analysis module is configured at a higher security level than the physical analysis module; and the one or more models is based on historical information corresponding to the physical diagnostic information and the cyber security data.

2. The system of claim 1 , wherein the model is constructed using machine learning techniques.

3. The system of claim 1 , wherein the cyber analysis module obtains the cyber security data via a cloud network structure.

4. A method comprising:
obtaining, via one or more sensors, physical diagnostic information describing at least one of an operational or environmental state of a functional system and further determining physical analysis information using the physical diagnostic information;
obtaining cyber security data corresponding to a networking portion of the functional system to determine cyber analysis information using the cyber security data;
obtaining, at a processing module, the physical diagnostic information and the cyber security data;
determining, at the processing module, a state of the functional system using the physical analysis information and the cyber analysis information, the state corresponding to at least one of physical condition or cyber security threat; and
identifying, at the processing module, if the state corresponds to one or more of a non-malicious condition or a malicious condition;
further comprising determining, at the processing module, an expected life for the functional system using at least a portion of the cyber security data, wherein the expected life is an expected secure life corresponding to a predicted time for which the functional system is expected to be secure from faults due to previous exposure to cyber attack;
wherein the step of obtaining the cyber security data is performed at a higher security level than the step of obtaining the physical diagnostic information; and further accounts for historical information corresponding to the physical diagnostic information and the cyber security data.

5. The method of claim 4 , wherein the model is constructed using machine learning techniques.

6. The method of claim 4 , wherein the physical diagnostic information and the cyber security data are obtained via a cloud network structure.

Assignees

• Gen Electric

Inventors

• Evans Scott Charles
• Arthur Richard Brownell
• Bouqata Bouchra
• Mishra Piyush
• Yan Weizhong
• Varma Anil

Classifications

• G06F21/55 Primary

  Detecting local intrusion or implementing counter-measures · CPC title

• G05B23/024

  Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks · CPC title