DocumentCode :
2297060
Title :
Application of data mining in fault diagnoses For machinery
Author :
Han, Yilun ; Ming, Sun
Author_Institution :
Inst. of Mechano-Electron. Eng., Shandong Univ. of Sci. & Technol., Qingdao, China
Volume :
3
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
1552
Lastpage :
1555
Abstract :
Data mining can draw out much useful knowledge and information unknown beforehand from amounts of uncompleted, unstable, random data. The paper studies the application about the technology of data mining based on wavelet theory in fault diagnosis for machinery according to up-to-date outcome, and brings forward the data mining way based on wavelet theory, we do verification by experiment. The wavelet transform can draw out the feature of fault, the neural network based on wavelet can effectively carry out the classification of faults. The basis can be supplied for its application.
Keywords :
data mining; fault diagnosis; machinery; mechanical engineering computing; neural nets; wavelet transforms; data mining application; fault diagnosis; machinery; neural network; up-to-date outcome; wavelet theory; wavelet transform; Artificial neural networks; Data mining; Gears; Vibrations; Wavelet analysis; Wavelet packets; mining; neural network; wavelet;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
Type :
conf
DOI :
10.1109/ICNC.2010.5583723
Filename :
5583723
Link To Document :
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