Fault diagnosis of automobile main reducer based on correlation dimension

Author(s):  
Pang Mao ◽  
Zhou Xiaojun ◽  
Yang Chenlong
Author(s):  
W Wang ◽  
J Chen ◽  
Z Wu

This paper reports on the application of the correlation dimension in large rotating machinery fault diagnosis. The Grassberger-Procaccia algorithm and its modified version are introduced. Some important influencing factors relating directly to the computational precision of the correlation dimension are discussed. Industrial vibration signals measured from large rotating machinery with different faults are researched using the above-mentioned methods. The results show that the correlation dimension can provide some intrinsic information on an underlying dynamic system and can be used to classify different faults intelligently.


IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 78483-78492 ◽  
Author(s):  
Changrui Chen ◽  
Tian He ◽  
Dengyun Wu ◽  
Qiang Pan ◽  
Hong Wang ◽  
...  

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