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The fault diagnosis of industrial equipment is the earliest application field of artificial intelligence technology. Pattern recognition and signal processing methods have been widely used, and excellent results have been achieved. However, the classical algorithm is also facing significant challenges: the data set is getting larger and larger, and the real-time requirement is increasing. It is one of the current hotspots for using the deep learning method to carry out this work.

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Equipment Fault Diagnosis and Preventive Maintenance

  • 章节

  • 发表日期：

    2025年

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  • Tianyuan Liu,
  • Jinsong Bao,
  • Yu Zheng,
  • Yuqian Lu

摘要

The fault diagnosis of industrial equipment is the earliest application field of artificial intelligence technology. Pattern recognition and signal processing methods have been widely used, and excellent results have been achieved. However, the classical algorithm is also facing significant challenges: the data set is getting larger and larger, and the real-time requirement is increasing. It is one of the current hotspots for using the deep learning method to carry out this work.