Industrial plant monitoring

US11971706B2 · kind B2 · utility

Assignee

• BASF SE

Inventors

• Nikolaos Fanidakis · Ludwigshafen, DE
• Claus-Juergen Neumann · Ludwigshafen, DE
• Benjamin Priese · Ludwigshafen, DE
• Frank Strohmaier · Ludwigshafen, DE
• Norman Volkert · Ludwigshafen, DE
• Thomas Christ · Auburn Hills, US
• Torsten Norbert Kneitz · Ludwigshafen, DE
• Alexander Kubisch · Ludwigshafen, DE

Key dates

• Filing date: Jan 29, 2021
• Grant date: Apr 30, 2024
• Expiry date: Jan 29, 2041

Classification

• Technology area (CPC Y): Emerging Cross-Sectional Technologies
• CPC primary: Y02P90/80
• WIPO field: Control
• WIPO sector: Instruments

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 …