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. 11, 2025

Filed:

Dec. 27, 2023
Applicant:

Honeywell International Inc., Charlotte, NC (US);

Inventors:

David Kucera, Bilovice nad Svitavou, CZ;

Curtis Taylor, Paradise Valley, AZ (US);

Jonathan Mcdonald, Shakopee, MN (US);

Gregory Stewart, North Vancouver, CA;

Wyatt Culler, Berne, IN (US);

Assignee:

HONEYWELL INTERNATIONAL INC., Charlotte, NC (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
F23N 5/24 (2006.01); F23N 5/16 (2006.01); F27D 21/04 (2006.01); G06F 16/21 (2019.01); G06N 5/02 (2023.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01); F27D 21/00 (2006.01); F27D 21/02 (2006.01);
U.S. Cl.
CPC ...
F27D 21/04 (2013.01); F23N 5/16 (2013.01); F23N 5/242 (2013.01); G06F 16/219 (2019.01); G06N 5/02 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); F23N 2223/04 (2020.01); F23N 2223/08 (2020.01); F23N 2223/36 (2020.01); F23N 2223/48 (2020.01); F23N 2229/00 (2020.01); F23N 2241/04 (2020.01); F23N 2900/05006 (2013.01); F27D 2021/0057 (2013.01); F27D 2021/026 (2013.01);
Abstract

A flame analytics system that may incorporate a burner, one or more sensors at the burner, a historical database connected to the one or more sensors, a model training module connected to the historical database, and a runtime algorithm module connected to the one or more sensors and the model training module. The runtime algorithm may compare realtime data from the one or more sensors and historical data from the model training module in accordance with a machine learning algorithm. The system may further incorporate a fault detection module connected to the runtime algorithm module, a fault diagnostics module connected to the fault detection module, and an enunciator connected to the fault detection module. The one or more sensors may also include having video or acoustic sensitivity of combustion in the burner.


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