
Survey on Advanced Equipment Fault Diagnosis and Warning Based on Big Data Technique
Author(s) -
Miao Wang,
Zhenming Zhang,
Kai Li,
Can Si,
Long Li
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1549/4/042134
Subject(s) - fault (geology) , big data , warning system , computer science , engineering , reliability engineering , data mining , telecommunications , seismology , geology
Faults are main problem of Mechanical equipment. In general, in order to acquire the massive fault information of equipment, a large number of monitoring points need to be established on the equipment, and the number of sensors for the equipment is large, since equipment fault diagnosis enter the era of big data. The successful application of big data technology in track circuit and power equipment system indicates that the big data of equipment contains important information that reveals the evolution and nature of faults. This paper briefly introduces the development of fault diagnosis technology from three aspects: data acquisition, intelligent fault diagnosis approach and remote fault diagnosis. In addition, This paper expounds the development history of fault diagnosis technology, analyzes the challenges of intelligent fault diagnosis in the era of big data, and discusses the development trend of equipment fault diagnosis according to the existing foundation and challenges. Finally, the development trend of equipment fault diagnosis and early warning are pointed based on existing research.