Data-Driven Methods for Predictive Maintenance of Industrial Equipment: A Survey

With the tremendous revival of artificial intelligence, predictive maintenance (PdM) based on data-driven methods has become the most effective solution to address smart manufacturing and industrial big data, especially for performing health perception (e.g., fault diagnosis and remaining life assessment). Moreover, because the existing PdM research is still in primary experimental stage, most works are conducted utilizing several open-datasets, and the combination with specific applications such as rotating machinery is especially rare. Hence, in this paper, we focus on data-driven methods for PdM, present a comprehensive survey on its applications, and attempt to provide graduate students, companies, and…

• NN
  National Natural Science Foundation of China

  Award: 61771040
• NK
  National Key Research and Development Program of China

  Award: 2018YFB1702001
• FR
  Fundamental Research Funds for the Central Universities

  Award: 2018YJS013