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:
Sep. 14, 2021

Filed:

Jan. 24, 2019
Applicant:

Jiangnan University, Wuxi, CN;

Inventors:

Xiaoli Luan, Wuxi, CN;

Niannian Zheng, Wuxi, CN;

Enbo Feng, Wuxi, CN;

Chenglin Liu, Wuxi, CN;

Fei Liu, Wuxi, CN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 5/04 (2006.01); G08B 21/18 (2006.01); G01M 13/003 (2019.01); G01M 99/00 (2011.01);
U.S. Cl.
CPC ...
G06N 5/048 (2013.01); G01M 13/003 (2019.01); G01M 99/005 (2013.01); G08B 21/187 (2013.01);
Abstract

The present invention discloses a multilevel pattern monitoring method for a process industry process and belongs to the fields of industrial production and processing. The multilevel pattern monitoring method comprises the steps: dividing an industry process into a plurality of levels from the view of patterns, selecting a different key performance index for each level, acquiring operating data relevant to the key performance index, identifying the pattern of each level, and proposing a pattern monitoring method for each level based on a data driven method to realize pattern monitoring in the industry process. The effect of rapidly finding a fault is achieved by monitoring real-time data according to the pattern, identified in a clustering plane, of each level, the effect of removing the fault is achieved by the selected N variables generating the greatest influence to the current pattern in combination with an expert system and an inference engine, meanwhile, the energy consumption of the process is reduced, the operating cost is optimized, and the competitiveness of a product is improved.


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