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:
Dec. 24, 2024

Filed:

Dec. 05, 2019
Applicant:

Abb Schweiz Ag, Baden, CH;

Inventors:

Mohak Sukhwani, Benares, IN;

Divyasheel Sharma, Bangalore, IN;

Sudarshan M V, Bangalore, IN;

Prabhat Shankar, Bangalore, IN;

Aravindhan Gk, Chennai, IN;

Assignee:

ABB Schweiz AG, Baden, CH;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
B25J 9/16 (2006.01); B25J 11/00 (2006.01);
U.S. Cl.
CPC ...
B25J 9/1674 (2013.01); B25J 9/161 (2013.01); B25J 9/163 (2013.01); B25J 9/1653 (2013.01); B25J 9/1664 (2013.01); B25J 11/0075 (2013.01);
Abstract

The present invention relates to a method and a system for detecting anomalies in a robotic system in an industrial plant. The robotic system is associated with a computing system configured to detect an anomaly in the robotic system. The computer system monitors configuration parameters of the robotic system and process parameters associated with the robotic system. Further, the computing system detects an association between at least one configuration parameter and at least one process parameter for obtaining optimal configuration parameters and optimal process parameters. The optimal configuration parameters and optimal process parameters are analyzed for detecting an anomaly. At least one parameter among the configuration parameters and the process parameters is identified causing the anomaly. Thereafter, the detected anomaly is validated, valid setpoint is estimated and the estimated valid setpoint is updated in the analytics model. The updated analytics model is subsequently used to detect anomaly accurately.


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