Method, system and paperboard production machine for estimating paperboard quality parameters

US12282012B2 · kind B2 · utility

Assignee

• Siemens Energy Global GmbH & Co. KG · DE

Inventors

• Adam Alpire · Erlangen, DE
• Thomas Eisenstecken · Erlangen, DE
• Michael Hildebrand · Mössingen, DE
• Ferdinand Kisslinger · Hersbruck, DE

Key dates

• Filing date: Aug 19, 2020
• Grant date: Apr 22, 2025
• Expiry date: Dec 2, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N20/00
• WIPO field: Measurement
• WIPO sector: Instruments

Abstract

A computer-implemented method for estimating at least one quality parameter of paperboard produced in a paperboard production subprocess of a paperboard processing pipeline by a data-driven module having a preprocessing module and a machine-learning module. Sensor data is acquired along the processing pipeline. Features are extracted from the sensor data by the preprocessing module. The machine-learning module is trained to reproduce target quality values from historical features. After training, the machine-learning module processes real-time features and estimates at least one quality parameter. A system implements the computer-implemented method and to a paperboard production machine includes such a system.