Open AccessMechanical equipment fault detection applying data mining technology
Author(s) -
Yiqun Liu,
Xiaogang Wang,
Xiaoyuan Gong,
Hua Mu
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 - 10.1088/1742-6596/1684/1/012024
Subject(s) - fault detection and isolation , field (mathematics) , process (computing) , fault (geology) , data mining , computer science , key (lock) , engineering , artificial intelligence , computer security , seismology , pure mathematics , actuator , geology , operating system , mathematics
Mechanical equipment fault detection in manufacturing enterprises has always been an important link in the manufacturing process. Along with the computer technology, artificial intelligence technology and various sensors are widely used in manufacturing industry, The amount of data produced by manufacturing machinery and equipment at all stages of the production process is also increasing rapidly, It is particularly important to analyze the data generated by these devices for fault detection and even prediction, Data mining technology provides advanced analysis methods for this purpose. This paper first introduces the basic concepts of Data Mining, Data Mining process and the key technology of Data Mining, and then focuses on the application of Data Mining in machinery fault detection, finally through the analysis of Data Mining in the field of top class meeting KDD2019, explored the could be applied to machinery fault detection of new technology, forecast the Data Mining technology in the fault detection of possible development trend.