Published April 4, 2024 | Version 1.0.0
Conference paper Open

Integrated Data Analytics and Regression Techniques for Real-time Anomaly Detection in Industrial Processes

  • 1. ROR icon Slovak University of Technology in Bratislava
  • 2. Slovnaft, a.s.

Description

In this paper, we present a data-based monitoring approach designed for industrial data classification, aiming to minimize misclassifications of normal operations and to maximize the detection of anomalies and outliers. We make use of movinghorizon approaches and regression methods. Through evaluation of various algorithms on an industrial dataset, we showcase the effectiveness of the classification. As per our findings, effective detection can only be realized in conjunction of moving-horizon estimator with a regression model trained on historical measurements. The best prediction models consistently achieve accurate detection within the approved process tolerance, highlighting the efficacy of the proposed approach.

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Additional details

Funding

European Commission
FrontSeat – Fostering Opportunities Towards Slovak Excellence in Advanced Control for Smart Industries 101079342
Slovak Research and Development Agency
Data Based Process Control APVV-21-0019
The Vega Science Trust
Efficient control of industrial plants using data VEGA 1/0691/21

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