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:
Apr. 30, 2024

Filed:

Jan. 29, 2021
Applicant:

Basf SE, Ludwigshafen, DE;

Inventors:

Nikolaos Fanidakis, Ludwigshafen, DE;

Claus-Juergen Neumann, Ludwigshafen, DE;

Benjamin Priese, Ludwigshafen, DE;

Frank Strohmaier, Ludwigshafen, DE;

Norman Volkert, Ludwigshafen, DE;

Thomas Christ, Ludwigshafen, DE;

Torsten Norbert Kneitz, Ludwigshafen, DE;

Alexander Kubisch, Ludwigshafen, DE;

Assignee:

BASF SE, Ludwigshafen am Rhein, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G05B 19/418 (2006.01);
U.S. Cl.
CPC ...
G05B 19/41875 (2013.01); G05B 2219/37591 (2013.01);
Abstract

The present teachings relate to a method comprising a plurality of sensors, and one or more functionally connected processing units, the method comprising: providing, at any of the one or more processing units, time-series residual data of a sensor object; the sensor object being a group of at least some of the sensors from the plurality of sensors, and wherein the residual data comprises, for each of the sensors of the sensor object, a residue signal which is a difference between the sensor's measured output and the sensor's expected output, monitoring, via any of the one or more processing units, a level signal; wherein the level signal is indicative of a collective time-based variation of the time-series residual data, monitoring, via any of the one or more processing units, an association signal; wherein the association signal is indicative of the variation and/or association structure of the time-series residual data, generating, via any of the one or more processing units, an anomaly event signal when at a given time a value of the level signal and/or a value of the association signal changes from an expected value of the respective signal at or around that time. The present teachings also relate to a monitoring and/or control system for a plant comprising a plurality of sensors, wherein the system comprises one or more processing units configured to perform the method steps of any of the steps herein disclosed, and a computer software product.


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