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Abstract <p>A concept of an intelligent vibration diagnostics system for technological equipment is developed based on a digital twin architecture, employing machine learning methods and integrated with Russian and international standards. This system enables a comprehensive assessment of the technical condition of equipment based on multiparametric data and residual life prediction using machine learning and degradation trend analysis.</p>

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Concept of a Digital Twin of Metalworking Equipment Using Machine Learning Methods in Vibration Diagnostics

  • 期刊论文

  • 发表日期：

    2026年2月1日

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  • S. A. Mantserov,
  • M. V. Zhelonkin,
  • D. A. Shatagin,
  • R. Sh. Mansurov

摘要

Abstract

A concept of an intelligent vibration diagnostics system for technological equipment is developed based on a digital twin architecture, employing machine learning methods and integrated with Russian and international standards. This system enables a comprehensive assessment of the technical condition of equipment based on multiparametric data and residual life prediction using machine learning and degradation trend analysis.