Research on Equipment Fault Identification Method and System based on Big Data Correlation Analysis


  • Dongxu Yang
  • Ran Huo
  • Jingquan Jia
  • Linxuan He



Big Data, Correlation Analysis, Equipment Fault Identification


With the rapid progress in the industrial field, equipment fault identification plays a crucial role in improving production efficiency and reducing operating costs. This article proposes a specialized and efficient equipment fault identification method and system based on big data correlation analysis. This system achieves precise identification of equipment faults by finely collecting and preprocessing equipment operation data, deeply exploring potential association rules between data. The method proposed in this article not only improves the accuracy of fault recognition, but also significantly enhances recognition efficiency, providing strong support for intelligent and refined management in the industrial field.


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How to Cite

Yang, D., Huo, R., Jia, J., & He, L. (2024). Research on Equipment Fault Identification Method and System based on Big Data Correlation Analysis. Frontiers in Computing and Intelligent Systems, 8(3), 80-83.