TY - GEN

T1 - I-STEP – A Case Study: Machine Learning powered Condition Monitoring of a Linear Motion Industrial Vibrating Screen

AU - Krukenfellner, Philip

AU - Flachberger, Helmut

PY - 2024/11/13

Y1 - 2024/11/13

N2 - Vibrating Screens, crucial in mineral and waste processing industries, usually lack adequate condition monitoring to assess condition states or predict machine errors. Addressing this issue, IFE Aufbereitungstechnik GmbH and its partners are developing "i-STEP," a digitalization solution potentially integrating any market-available sensor for a customizable, plant-wide monitoring platform. Thus far, a vibration sensor, "SES" has been developed to specifically measure oscillation patterns of vibrating screens, which is the main focus of this research.

AB - Vibrating Screens, crucial in mineral and waste processing industries, usually lack adequate condition monitoring to assess condition states or predict machine errors. Addressing this issue, IFE Aufbereitungstechnik GmbH and its partners are developing "i-STEP," a digitalization solution potentially integrating any market-available sensor for a customizable, plant-wide monitoring platform. Thus far, a vibration sensor, "SES" has been developed to specifically measure oscillation patterns of vibrating screens, which is the main focus of this research.

KW - Schwingsiebe

KW - Schwingungsüberwachung

KW - Zustandsüberwachung

KW - Machine Learning

KW - Vibration Screens

KW - Vibration monitoring

KW - Condition monitoring

KW - Machine learning

M3 - Conference contribution

SN - 978-3-200-09925-8

SP - 529

EP - 534

BT - VORTRÄGE-Konferenzband

CY - Leoben

T2 - Recy & Depotech 2024

Y2 - 13 November 2024 through 15 November 2024

ER -