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This research article is dedicated to the detection and diagnosis of potential equipment failures. Machine learning and artificial intelligence methods are used for diagnostics. An example of industrial equipment is a DC motor tested in the laboratory under different conditions with simulated failures. Several data reduction methods are used to work with this database. The data obtained after data reduction will be compared after that the data will be tested on predictive models with an alignment of the effectiveness of the combination of the reduction method and the predictive model. Comparing all the results, the most effective combination of methods with the highest metrics will be selected.

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Development of a Predictive Analytics Model for Diagnosing Industrial Equipment Failures Using Artificial Intelligence Methods

  • 会议论文

  • 发表日期：

    2025年

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  • G. A. Samigulina,
  • Z. I. Samigulina,
  • D. D. Bekeshev

摘要

This research article is dedicated to the detection and diagnosis of potential equipment failures. Machine learning and artificial intelligence methods are used for diagnostics. An example of industrial equipment is a DC motor tested in the laboratory under different conditions with simulated failures. Several data reduction methods are used to work with this database. The data obtained after data reduction will be compared after that the data will be tested on predictive models with an alignment of the effectiveness of the combination of the reduction method and the predictive model. Comparing all the results, the most effective combination of methods with the highest metrics will be selected.