REVIEW OF FAULT DIAGNOSIS METHODS FOR ROTATING MACHINERY BASED ON DEEP LEARNING

Abstract

Mechanical equipment fault diagnosis technology is a new research field with the development of modern science and technology In recent years, the deep learning has been applied into the field of mechanical equipment fault diagnosis by more and more researchers. Deep learning has been widely applied in various in dustries and fields with its unique advantages in feature extraction and pattern recognition. The development history of deep learning is first briefly reviewed. Then, four fault diagnosis methods based on deep learning model are emphatically analyzed com bined with the characteristics and requirements of fault diagnosis technology for large rotating machinery equipment, and the problems and challenges they face are discussed. Finally, the research direction worth to be carried out in the future is prospected.