DocumentCode :
478128
Title :
Intelligent Modeling of Abnormal Vibration for Large-Complex Machine Based on Chaos and Wavelet Neural Networks
Author :
Luo, Zhonghui
Author_Institution :
Sch. of Mechatron. Eng., Guangdong Polytech. Normal Univ., Guangzhou
Volume :
2
fYear :
2008
fDate :
18-20 Oct. 2008
Firstpage :
439
Lastpage :
442
Abstract :
This paper analyses the chaotic characteristics of a large temper rolling millpsilas abnormal vibration signals, and studies phase space reconstruction techniques of the signals. Then, combining the theory of chaotic dynamics and wavelet neural networks, a new vibration model is set up, through inversion method. The property of the model is tested and compared with the model of backpropagation(BP) neural networks, respectively. The result shows that the wavelet neural networks have an advantage over the backpropagation neural networks in rapid convergence and high accuracy.
Keywords :
backpropagation; chaos; machinery; mechanical engineering computing; neural nets; rolling mills; vibrations; wavelet transforms; abnormal vibration; backpropagation neural networks; chaos; chaotic dynamics; inversion method; large-complex machine; phase space reconstruction techniques; wavelet neural networks; Chaos; Delay effects; Frequency; Intelligent networks; Machine intelligence; Mathematical model; Milling machines; Neural networks; Shafts; Testing; Modeling; Phase space reconstruction; Vibration; Wavelet neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
Type :
conf
DOI :
10.1109/ICNC.2008.715
Filename :
4667033
Link To Document :
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