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Multi-working condition performance assessment based on knowledge extraction of optimal operating states for continuous annealing processes

Author

Listed:
  • Jiang He
  • Weihua Cao
  • Wenkai Hu
  • Wenshuo Song
  • Min Wu

Abstract

Performance assessment is a key to strip quality improvement and energy consumption reduction of Continuous Annealing Processes (CAP). However, existing methods focus on performing the assessment under a single working condition, and the assessment accuracy must be improved. This study proposes a new multi-working-condition performance assessment method based on the knowledge extraction of the optimal operating states for CAP. First, a mechanism–data fusion-based assessment index construction method is proposed for the key parameter selection. Second, a knowledge extraction strategy for the optimal operating states under multiple working conditions is proposed to construct a benchmark library. Third, a knowledge-enhanced assessment model is built to achieve qualitative performance evaluation and quantitative non-optimal traceability. The experiment based on the process data shows the effectiveness of assessing the operating performance, providing decision guidance for strip quality improvement and energy consumption reduction.

Suggested Citation

  • Jiang He & Weihua Cao & Wenkai Hu & Wenshuo Song & Min Wu, 2024. "Multi-working condition performance assessment based on knowledge extraction of optimal operating states for continuous annealing processes," International Journal of Systems Science, Taylor & Francis Journals, vol. 55(5), pages 894-908, April.
  • Handle: RePEc:taf:tsysxx:v:55:y:2024:i:5:p:894-908
    DOI: 10.1080/00207721.2023.2300718
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