US 12,443,177 B2
Analysis method and devices for same
Andreas Gienger, Kirchheim unter Teck (DE); Oliver Sawodny, Stuttgart (DE); Simon Alt, Ditzingen (DE); Martin Weickgenannt, Bietigheim-Bissingen (DE); Markus Hummel, Urbach (DE); Tobias Schlotterer, Hechingen (DE); Jens Berner, Möglingen (DE); and Hauke Bensch, Lübeck (DE)
Assigned to Dürr Systems AG, Bietigheim-Bissingen (DE)
Appl. No. 17/608,473
Filed by Dürr Systems AG, Bietigheim-Bissingen (DE)
PCT Filed Apr. 29, 2020, PCT No. PCT/DE2020/100358
§ 371(c)(1), (2) Date Nov. 2, 2021,
PCT Pub. No. WO2020/224716, PCT Pub. Date Nov. 12, 2020.
Claims priority of application No. 10 2019 112 099.3 (DE), filed on May 9, 2019; and application No. 10 2019 206 837.5 (DE), filed on May 10, 2019.
Prior Publication US 2022/0214676 A1, Jul. 7, 2022
Int. Cl. G05B 23/02 (2006.01)
CPC G05B 23/0254 (2013.01) [G05B 2223/02 (2018.08)] 28 Claims
OG exemplary drawing
 
1. A method for anomaly and/or fault recognition in an industrial process, the method comprising:
identifying a process structure of the industrial process comprising determining a structure graph mapping relationships of components, in the industrial process;
wherein the components comprise sensors and/or actuators;
wherein the structure graph comprises a plurality of cliques describing physical relationships between the components, and wherein relationships between nodes of each are described by a probability density function of a plurality of probability density functions;
generating an anomaly and/or fault model of the industrial process, wherein the anomaly and/or fault model comprises the structure graph;
the anomaly and/or fault model comprising information on an occurrence probability of process values of the industrial process;
inputting the process values of the industrial process into the anomaly and/or fault model during operation of the industrial process,
using the probability density functions to recognize an anomaly and/or fault situation by determining the occurrence probability of the inputted process values of the industrial process and by checking the occurrence probability against a limit value; and
applying at least one corrective measure based on the recognized anomaly and/or fault situation and/or continuing operation of the industrial process.